Legal Workflow Automation Executive

Legal Workflow Specialist

Forward Deployed AI Strategist

Account Manager

Staff/Principal Engineer, NAND TD, RDA

Senior Software Engineer AI

Software Engineer AI

Data & ML Architect

Manager, Data Science - Agentic AI

Senior Data Scientist III - Agentic AI

Role Description: <ul><li>As a Legal Workflow Automation Executive , you collaborate closely with top legal teams to leverage Generative AI in automating legal processes—designing intelligent workflows that streamline operations, enhance efficiency, and empower firms to make more informed decisions.</li><li>Your role centres on identifying automation opportunities, demonstrating practical AI-driven solutions, and guiding adoption to ensure measurable improvements from initial implementation through to scalable impact.</li></ul> Responsibilities: <ul><li>Partner with lawyers and legal operations leaders to unpack real world legal workflows, pain points, and inefficiencies.</li><li>Translate legal work into high value workflow use cases supported by AI and trusted legal content.</li><li>Design and deliver tailored product demonstrations, training sessions, and workshops aligned to specific practice areas and team needs.</li><li>Support the full client journey in partnership with Customer Success — from pilots and onboarding to firm wide or department wide adoption.</li><li>Act as a strategic sounding board for clients evaluating the ROI, risk, and operational impact of AI in legal practice.</li><li>Represent the customer internally by feeding insights into product development, roadmap prioritisation, and go to market strategy.</li><li>Capture best practices and contribute to repeatable playbooks that help scale this function locally and globally.</li></ul> Requirements: <ul><li>A recognised legal qualification (LLB or equivalent).</li><li>A minimum of 3 years’ experience practising law within a top tier law firm, corporate legal team, or public sector legal environment.</li><li>A strong understanding of legal workflows, legal processes, and the practical realities of delivering legal services.</li><li>Proven confidence engaging with senior legal stakeholders, with the ability to establish trust and credibility quickly.</li><li>Clear, persuasive communication skills, with the ability to engage legal, operational, and executive audiences effectively.</li><li>A genuine interest in legal technology and the application of AI to enhance the quality and efficiency of legal work.</li></ul>

Responsibilities: <ul><li>Design and deliver onboarding tailored to South African firms, practice groups, and in‑house legal teams.</li><li>Lead interactive training sessions that demonstrate AI‑enabled workflows across research, drafting, review, and knowledge management</li><li>Create clear, practical training materials, including guides and short videos.</li><li>Engaging in-house legal teams to understand their daily workflows and creating tailored AI solutions (e.g., Protégé Workflows) to enhance existing processes, improve outcomes, and increase productivity and ROI.</li><li>Monitor product usage across SA clients and drive increased utilisation, particularly in high‑volume corporate, regulatory, and litigation practices.</li><li>Identify adoption obstacles specific to SA legal environments</li><li>Demonstrate measurable client value, including efficiency gains, quality improvements, risk reduction and consistency.</li><li>Work with customers to understand existing processes and design improved, AI‑supported workflows.</li><li>Configure workflows to align with client preferences, practice‑area needs, and organisational standards.</li><li>Share proven approaches and best practices to support learning across the customer base.</li><li>Represent customer perspectives internally, translating feedback into clear, practical insights.</li><li>Partner with product and development teams to inform future improvements.</li><li>Support testing of new features, focusing on usability, accuracy, and real‑world application.</li></ul> Requirements: <ul><li>Admitted Attorney (LLB required; articles completed).</li><li>2–5+ years post‑admission</li><li>Exposure to complex legal workflows—corporate, commercial, litigation, regulatory or similar.( advantageous)</li><li>Confidence communicating with a range of stakeholders and delivering clear, engaging presentations or training</li><li>Ability to “translate” legal workflows into repeatable, technology‑enabled processes.</li><li>An interest in legal technology and curiosity about how AI can support better legal outcomes</li><li>Excellent relationship‑building, active listening and stakeholder‑management skills.</li><li>Data‑driven mindset with the ability to articulate value and ROI</li></ul>

Role Description: <ul><li>The Strategy team is looking for a hands-on AI-enabled strategy and market intelligence professional to materially accelerate the way we conduct deep research, market intelligence, analytical modeling, and GTM analysis by applying high impact AI workflows and translating them into sharper strategic decisions.</li><li>The individual will partner with business, product, commercial, and tech teams to translate ambiguous questions into actionable insights, while developing and scaling AI-enabled solutions that improve strategic decision-making and drive measurable business impact.&nbsp;</li><li>The individual is expected to work in close partnership with our client IT team, to leverage existing AI &amp; data capabilities on Databricks &amp; AWS (where applicable) while developing solutions.</li></ul> Responsibilities: Strategic problem solving and driving cross-functional execution&nbsp; <ul><li>Translate AI-assisted analyses into practical executive decisions by applying strong business judgment, rigorous validation protocols, and a sharp “so-what” orientation</li><li>Collaborate with and influence senior stakeholders across strategy, sales, technology teams, and P&amp;L owners</li><li>Good first-principles and problem-solving capabilities with the ability to build and test strategic hypotheses Identifying meaningful opportunities to leverage AI and deploying scaled AI solutions at pace</li></ul> Identify, assess, and prioritize high-value AI and automation opportunities by translating business challenges into scalable, practical solutions&nbsp; <ul><li>Design proprietary AI-enabled workflows, agents, and accelerators for recurring strategy activities (competitor monitoring, earnings call tracking, tariff and regulatory intelligence, voice-of-customer mining etc.)</li><li>Build reusable templates, workflows, and modules to drive adoption and embed AI capabilities into strategy processes</li></ul> Executing rapid AI-augmented research and competitive intelligence&nbsp; <ul><li>Lead AI-augmented research using tools like Claude, OpenAI, Perplexity, AlphaSense, CapIQ etc. to deliver source-triangulated competitive and industry insights</li><li>Synthesize structured datasets (S&amp;P Capital IQ, Bloomberg, IDC, Gartner) and unstructured sources (10-Ks, analyst reports, expert interviews) – to generate and validate AI-assisted outputs</li></ul> Support strategy team in day-to-day execution by leveraging AI-led tools <ul><li>Lead AI-enabled market sizing, opportunity mapping, and TAM/SAM/PAM modelling</li><li>Accelerate financial modelling – scenario and sensitivity analyses, valuation, NPV/IRR, segment P&amp;Ls, pricing</li><li>Support M&amp;A pipeline by AI-screening targets and generating investment theses</li></ul> AI enablement, coaching and continuous innovation <ul><li>Coach strategy team members on prompting techniques, research workflows, and AI-fluent execution</li><li>Scale AI adoption across Corporate Strategy through hands-on mentorship of beginner users</li><li>Stay current on agentic stacks, multimodal models, and deep research agents</li></ul> Requirements: Skillset and capabilities AI fluency and hands-on deployment orientation&nbsp; <ul><li>Working knowledge of GenAI patterns – LLM capabilities/limitations, prompt design, etc.</li><li>Proven ability to convert business problems into reusable AI workflows, tools, or accelerators</li><li>Builder mindset with experience prototyping AI solutions using frontier tools &amp; low-code platforms</li></ul> Analytics, modelling, and research excellence <ul><li>Strong modelling skills across TAM/SAM/PAM, scenarios, sensitivities, NPV/IRR, valuation etc.</li><li>Ability to synthesize structured datasets with unstructured sources</li><li>Research discipline – source triangulation and rigorous validation of AI outputs</li></ul> Strategic problem solving, communication, executive presence, and influence&nbsp; <ul><li>Sharp "so-what" orientation to translate AI outputs into practical executive decisions</li><li>Crisp written and verbal communication, with ability to frame board-ready narratives</li><li>Skill in explaining AI workflows and implications to both technical and non-technical audiences</li><li>Stakeholder management across strategy, commercial, data, and technology teams</li></ul> Ownership, and execution <ul><li>Independently own workstreams end-to-end – from framing through deployment</li><li>High bar for quality; never publishes unchecked AI outputs or unvalidated analysis</li></ul> Coaching and capability building&nbsp; <ul><li>Patience and ability to coach colleagues on prompting, research workflows, and source validation</li><li>Track record of building reusable playbooks – templates and training modules that scale adoption</li></ul> Passion, curiosity, and learning agility <ul><li>Deep passion for AI, tech, and industrial innovation, with curiosity to stay current on frontier tools</li><li>Entrepreneurial ownership mindset and drive to build a new AI-enabled strategy capability</li></ul> Qualifications:&nbsp; <ul><li>BE / B-Tech in Computer Science Engineering, Data Science or a related analytical field required; MBA, MS, M-Tech or equivalent advanced degree strongly preferred.</li><li>3–4+ years of experience in AI transformation, analytics, or AI-enabled business building. Prior Forward Deployed Engineer / Solutions Architect / Senior Data Scientist background preferred.</li><li>Experience in a top-tier strategy consulting firm, AI-native consulting team, analytics firm or corporate / product strategy team role strongly preferred.</li><li>Demonstrated experience building or deploying 0–1 AI solutions (not just experimenting), GenAI, analytics, automation, or workflow solutions in a business environment required.</li><li>Proficiency in Excel and PowerPoint required; Python or equivalent scripting capability strongly preferred. Experience with DevOps, CI/CD pipelines, and infra as code (e.g., Jenkins, Docker, Kubernetes) required.</li><li>Proficient in implementing AI platforms like AWS Bedrock, LangGraph, Crew AI, Glean etc.</li><li>Knowledge of enterprise data environments (esp. SAP, Databricks) or cloud platforms (esp. AWS) is a plus. Experience integrating AI systems with enterprise data platforms required.</li><li>Experience with LLM-powered solutions, RAG systems, agentic workflows, AI research tools, or AI-enabled knowledge manage</li></ul>

Role Description: <ul><li>The Account Manager will be responsible for driving sales growth and managing customer relationships for the Industrial &amp; Commercial Transportation (ICT) Business Unit in West India. The role focuses on developing strong relationships with existing and new OEM and Tier-1 customers, identifying new business opportunities, increasing market share and ensuring customer satisfaction.</li><li>The Account Manager will work closely with cross-functional teams to support customers from concept development through production. </li><li>The Account Manager, West India – ICT Business Unit will be responsible for driving business growth and customer engagement in alignment with our client SET Methodology – Strategy, Execution, and Talent.</li></ul> Responsibilities: Strategy <ul><li>Develop and maintain strong long-term relationships with OEM and Tier-1 customers across the region.</li><li>Understand customer roadmaps, market trends and industry developments to identify growth opportunities.</li><li>Create and execute account strategies that support our client business objectives.</li><li>Identify new customers, applications and programs that can drive growth.</li><li>Increase our client market share through product spec-in, product conversion and competitive replacement opportunities.</li><li>Promote our client proposition and strengthen brand presence within customer organizations.</li><li>Monitor competitor activities and provide market intelligence to support business decisions.</li><li>Support value engineering and cost optimization initiatives that create mutual benefit for customers and our client .</li></ul> Execution <ul><li>Achieve assigned sales, revenue and growth targets.</li><li>Develop and maintain a strong opportunity pipeline and ensure timely conversion of opportunities.</li><li>Manage customer opportunities from concept stage through production launch.</li><li>Prepare accurate sales forecasts and support business planning activities.</li><li>Lead commercial discussions including pricing, negotiations and agreement execution.</li><li>Coordinate with Engineering, Product Management, Operations, Supply Chain and Customer Service teams to ensure customer requirement are fulfilled.</li><li>Drive timely collection of receivables and support healthy financial performance.</li><li>Prepare and maintain account plans for key customers.</li><li>Ensure accurate reporting and opportunity management through Salesforce (SFDC).</li><li>Deliver an exceptional customer experience through proactive engagement.</li></ul> Talent <ul><li>Build strong working relationships across regional and global teams.</li><li>Collaborate effectively with cross-functional stakeholders to achieve business objectives.</li><li>Share customer insights and market knowledge with internal teams to support strategic decision making.</li><li>Demonstrate our client values through teamwork, accountability, integrity and customer focus.</li><li>Act as a trusted advisor to customers and an effective representative of our client in the market.</li><li>Continuously develop commercial, technical, and industry knowledge to support long-term business growth.</li></ul> Requirements: EDUCATION/KNOWLEDGE <ul><li>Bachelors Degree (BE/B.Tech) in Mechanical, Electrical, Electronics, Mechatronics or related Engineering discipline.</li><li>MBA is preferred but not mandatory.</li><li>3–5 years of experience in Sales, Business Development, Account Management or Application Engineering.</li><li>Experience in the Automotive, Commercial Vehicle, Off-Highway, Industrial Vehicle or Automotive Components industry is preferred.</li><li>Exposure to OEM and Tier-1 customer management will be an advantage.</li><li>Strong commercial understanding and customer-facing experience.</li><li>Knowledge of automotive product development cycles is desirable.</li><li>Familiarity with CRM tools such as Salesforce is preferred.</li></ul>

Responsibilities: <ul><li>Own the site-level RDA strategy and annual roadmap aligned to NAND TD technology nodes.</li><li>Lead analysis of experimental and production flows to detect, classify, and trend systematic and random defects.</li><li>Establish, track, and report program health metrics (baseline health, detection rates, false positives, MTTR).</li><li>Direct fast containment for defect excursions: trigger tool quarantines, define hold criteria, and lead 8D corrective actions.</li><li>Architect inspection recipes and sampling strategies; optimize sensitivity, throughput, and cost of ownership.</li><li>Partner with Process Integration, Yield, and Data Science to correlate inspection signals to device performance and yield.</li><li>Influence supplier roadmaps; evaluate, qualify, and release next gen optical/e-beam inspection capabilities.</li><li>Standardize and disseminate Best Known Methods (BKM) across global TD and manufacturing sites.</li><li>Mentor, coach, and upskill engineers; develop succession plans and technical ladders within the RDA domain.</li><li>Champion safety and continuous improvement (CIP); drive kaizen/lean initiatives that improve cycle time and learning velocity.</li></ul> Requirements: <ul><li>Bachelor’s degree with 7+ years relevant semiconductor experience, or Master’s/PhD with 5+ years.</li><li>Minimum 3+ years hands-on RDA experience in semiconductor manufacturing or equipment engineering.</li><li>Demonstrated expertise in defect inspection, process monitoring, and yield learning.</li></ul> Technical Competencies <ul><li>Realtime Defect Analysis (RDA) systems and workflows.</li><li>Optical and e-beam inspection technologies.</li><li>Statistical data analysis, correlation development, and large dataset interpretation.</li><li>Semiconductor process integration and technology development.</li><li>Root cause analysis and systematic problem solving (e.g., 8D, DMAIC).</li><li>Leadership &amp; Behavioral Competencies</li><li>Recognized technical authority with the ability to influence without direct authority.</li><li>Strong mentoring and coaching mindset with proven talent development outcomes.</li><li>Clear, concise communication skills across technical and executive audiences.</li><li>Ownership-driven, execution-focused; comfortable operating in ambiguity.</li><li>Impact &amp; Success Measures</li><li>Reduced defect-related yield loss and faster learning cycles.</li><li>On-time qualification and adoption of next-generation inspection capabilities.</li><li>Uplift in organizational RDA skill depth and succession pipeline.</li><li>Alignment of inspection strategy and capability to future NAND nodes.</li></ul>

Responsibilities: Design &amp; Build/Development &amp; Support <ul><li>Develop multi-agent workflow automation patterns using Agentic AI</li><li>Process redesign and mapping to agentic workflow patterns</li><li>Architect scalable micro-services that wrap LLM/RAG/Agent workflows (Python).</li><li>Implement robust prompt-engineering patterns, retrieval pipelines, and caching for AI Assistants and AI Agents</li><li>Profile inference latency, GPU/CPU utilization, and memory</li><li>Writes and maintains highly complex unit tests and integration tests, and performs debugging to maintain the quality and performance of the software/AI solutions</li><li>Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents</li><li>Leads the establishment and maintenance of comprehensive documentation for agents, applications, deployment processes and system configurations.</li></ul> Operational Excellence&nbsp;<ul><li>Own on-call runbooks, SLOs, and incident reviews; embed observability</li><li>Leads and mentors technical support and troubleshooting for highly complex issues with deployed applications to ensure minimal downtime and fast resolution.&nbsp;</li></ul> Collaboration &amp; Leadership <ul><li>Leads cross functional team of engineers to gather requirements and deliver solutions that meet business needs.</li><li>Experience working within product and agile delivery frameworks including backlog management and cross-functionality delivery and full E2E engineering.&nbsp;</li><li>Experience with enterprise architecture, data governance, or security standards in the context of digital solution delivery as part of E2E engineering and solution architecture.&nbsp;</li></ul> Capability &amp; Technology Stack Exposure <ul><li>Experience with digital technologies in the commercial &amp; sales management capability (e.g. Salesforce, Service Cloud, CPQ, Salesloft, ChatGPT or similar platforms)&nbsp;</li></ul> Requirements: <ul><li>Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.&nbsp;</li><li>Typically reflects 4 years or more with 3+ years of cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP) or 2+ years of software development.&nbsp;</li></ul>

Responsibilities: Design &amp; Build/Development &amp; Support <ul><li>Develop multi-agent workflow automation patterns using Agentic AI</li><li>Process redesign and mapping to agentic workflow patterns</li><li>Architect scalable micro-services that wrap LLM/RAG/Agent workflows (Python).</li><li>Implement robust prompt-engineering patterns, retrieval pipelines, and caching for AI Assistants and AI Agents</li><li>Profile inference latency, GPU/CPU utilization, and memory</li><li>Writes and maintains highly complex unit tests and integration tests, and performs debugging to maintain the quality and performance of the software/AI solutions</li><li>Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents</li><li>Leads the establishment and maintenance of comprehensive documentation for agents, applications, deployment processes and system configurations.</li></ul> Operational Excellence&nbsp;<ul><li>Own on-call runbooks, SLOs, and incident reviews; embed observability</li><li>Leads and mentors technical support and troubleshooting for highly complex issues with deployed applications to ensure minimal downtime and fast resolution.&nbsp;</li></ul> Collaboration &amp; Leadership <ul><li>Leads cross functional team of engineers to gather requirements and deliver solutions that meet business needs.</li><li>Experience working within product and agile delivery frameworks including backlog management and cross-functionality delivery and full E2E engineering.&nbsp;</li><li>Experience with enterprise architecture, data governance, or security standards in the context of digital solution delivery as part of E2E engineering and solution architecture.&nbsp;</li></ul> Capability &amp; Technology Stack Exposure <ul><li>Experience with digital technologies in the commercial &amp; sales management capability (e.g. Salesforce, Service Cloud, CPQ, Salesloft, ChatGPT or similar platforms)&nbsp;</li></ul> Requirements: <ul><li>Minimum requirement of 2 years of building production software or data platforms.&nbsp;</li><li>Typically reflects 3 years or more with 2+ years of cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP) or 2+ years of software development.&nbsp;</li></ul>

Responsibilities: Strategic Leadership: <ul><li>Set the vision and direction for data and AI architecture for project and client.</li><li>Influence enterprise data and AI strategies, driving adoption of best practices in data, ML, and AI architecture.</li><li>Mentor and develop junior architects and engineers, fostering a culture of technical excellence and innovation.</li></ul> Architectural Excellence: <ul><li>Architect and design enterprise-scale data platforms and ML/AI solutions for scalability, reliability, and performance.</li><li>Define and enforce data and ML architecture standards, patterns, and governance frameworks for data pipelines, ML workflows, and analytics platforms.</li><li>Lead solution design for integrating data from diverse sources (streaming, batch, cloud, on-premises) using Azure, AWS, and GCP services.</li></ul> AI &amp; ML Leadership: <ul><li>Architect advanced Data Science, ML and AI solutions, including NLP, RAG LLM and Agentic AI systems.</li><li>Oversee the implementation of MLOps frameworks, ensuring robust deployment, monitoring, and lifecycle management of ML models.</li><li>Evaluate and recommend emerging AI/ML technologies and platforms, driving innovation in intelligent data products.</li><li>Provide Ethical AI leadership to ensure intelligent solutions are implemented when required and in safe methods.</li></ul> Technical Leadership: <ul><li>Oversee data modelling (e.g. medallion architecture), data governance, and quality frameworks. Implementing technical reviews and driving high standards.</li><li>Collaborate with engineering and DevOps teams to establish CI/CD and MLOps architectures using Azure DevOps, Kubernetes, and Terraform.</li><li>Guide the selection and implementation of visualization and analytics tools (Power BI, Tableau, PowerApps).</li></ul> Stakeholder Engagement: <ul><li>Engage with senior stakeholders to translate complex business requirements into technical solutions and strategic roadmaps.</li><li>Ensure all solutions meet security, compliance, and performance standards, and align with enterprise architecture principles.</li></ul> Innovation &amp; Emerging Technologies: <ul><li>Apply modern data and AI architecture patterns (Cloud Native, Steaming/batch ingestion, Agentic AI Design) and leverage platforms such as AI/ML, Big Data, and Data Lakehouse.</li></ul> Requirements: <ul><li>Minimum 8 years’ experience client facing roles specializing in Data and Architecture roles.</li><li>Experience in both Agile and Waterfall project environments.</li><li>Strong stakeholder management and communication skills.</li><li>Security and compliance awareness.</li><li>Industry certifications (e.g., AWS Solution Architect, Azure Data Engineer, GCP Data Engineer).</li><li>Experience mentoring or managing technical teams.</li></ul>

Responsibilities: <ul><li>Leading development of advanced AI Agentic tech.</li><li>Working closely with other data scientists and engineers to design, develop, and deploy AI solutions.</li><li>Collaborating with cross-functional teams to ensure AI solutions are aligned with business goals and customer needs.</li><li>Analyzing large datasets to identify patterns and trends that can inform AI development.</li><li>Communicating findings and insights to stakeholders in a clear and concise manner.</li><li>Staying current with the latest AI and machine learning trends and technologies.</li><li>Mentoring junior data scientists and provide guidance on AI and machine learning best practices</li><li>Driving best practices across our data science functions.</li><li>Setting strategy and team direction, with a clear vision for Data Science.</li><li>Working with product leaders to apply data science solutions..</li><li>Evaluating and creating new frameworks and defining methodologies and governance.</li><li>Leading small- to medium-sized teams (direct or indirect).</li><li>Setting a high bar for model development.</li></ul> Requirements: <ul><li>3+ years of people management experience.</li><li>7+ years of AI/ML experience.</li><li>Significant experience in managing larger technical teams (direct or indirect).</li><li>Have experience in mentoring or training others, acting as a subject matter expert to guide colleagues.</li><li>Be a natural problem solver, able to take a lead in collaborating to resolve issues.</li><li>Have excellent communication skills and the ability to convey information clearly to senior stakeholders.</li><li>Deep understanding of machine learning algorithms, including deep learning, gradient boosting, and random forests.</li><li>Experience working directly with large language models and Transformer based architectures including BERT, RoBERTa, T5 etc.</li><li>Working knowledge of applying recent LLMs including ChatGPT, GPT 3.5, OPT, BLOOM, etc.</li><li>Experience with reinforcement learning, prompt engineering, hallucination mitigation.</li><li>Working understanding of the business risks associated with applying LLM in a business.</li><li>Experience working with large datasets and distributed computing systems (e.g., Hadoop, Spark).</li><li>Strong coding skills in Python or another programming language.</li><li>Excellent communicator, with the ability to translate complex technical concepts to non-technical stakeholders.</li></ul>

Responsibilities: <ul><li>Lead experimentation and model development for AI/ML solutions in legal products.</li><li>Design and evaluate NLP, LLM, and generative AI approaches (e.g., RAG, prompt strategies).</li><li>Define agentic workflows and reasoning strategies for multi-step legal tasks.</li><li>Define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Analyze large-scale legal datasets to extract insights and improve model performance.</li><li>Establish best practices for model evaluation, validation, and benchmarking.</li><li>Translate experimental results into clear product recommendations and business impact.</li><li>Collaborate with product, legal experts, and engineers to align solutions with user needs.</li><li>Mentor team members and provide technical leadership in data science and AI.</li></ul> Requirements: <ul><li>Bachelor’s or Master’s degree in a relevant field (e.g., Computer Science, Data Science, Statistics, Mathematics).</li><li>Strong experience in machine learning, NLP, and LLM-based modeling.</li><li>Proven experience designing and running experiments, including model evaluation and iteration.</li><li>Experience with generative AI techniques (e.g., prompt engineering, RAG).</li><li>Experience designing and evaluating hybrid search (semantic + lexical) using embeddings and vector databases.</li><li>Experience designing agentic workflows and reasoning strategies, with hands-on experience applying agent frameworks (e.g., LangChain, LangGraph, AutoGen) in real-world use cases.</li><li>Proficiency in Python and data analysis tools.</li><li>Ability to define retrieval strategies, including hybrid search (semantic + lexical), and evaluation metrics (e.g., relevance, ranking quality).</li><li>Able to analyze large-scale legal datasets to extract insights and improve model performance.</li></ul>

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36 gen ai Jobs found

Legal Workflow Automation Executive

Legal Workflow Specialist

Forward Deployed AI Strategist

Account Manager

Staff/Principal Engineer, NAND TD, RDA

Senior Software Engineer AI

Software Engineer AI

Data & ML Architect

Manager, Data Science - Agentic AI

Senior Data Scientist III - Agentic AI

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Legal Workflow Automation Executive

Legal Workflow Specialist

Forward Deployed AI Strategist

Account Manager

Staff/Principal Engineer, NAND TD, RDA

Senior Software Engineer AI

Software Engineer AI

Data & ML Architect

Manager, Data Science - Agentic AI

Senior Data Scientist III - Agentic AI

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