Forward Deployed AI Strategist

Senior Production Support Engineer – IDM Engineering (VP2)

Data Analyst

Principal/Staff, Firmware and Product Test (SSD)

Senior Software Engineer AI

Software Engineer AI

Manager, Data Science - Agentic AI

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Senior Data Engineer

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>

Responsibilities: <ul><li>Engage in day-to-day support activities including incident and problem management</li><li>Perform production deployments, patch activities on the supported applications and servers.</li><li>Work with product support/development team for permanent resolution/change review – all types including enhancements, bug fixes, etc.</li><li>Work with level 1 support in application knowledge transfer in establishing standard first level recovery process/system health check monitoring/scheduled activities as well as common application user queries.</li><li>Collaborate with internal stakeholders like application, business, infrastructure, security, and operations to continuously improve the stability of applications.</li><li>Develop support operational documents to summarize common support issues.</li><li>Develop reports and drive audit RFI’s and requirements.</li><li>Develop Linux scripts based on the requirements.</li><li>Provide after office hours’ standby support and for emergency recoveries, including managing major incident of critical services.</li><li>Expected to drive improvements through influence and strong relationships with managers in other teams.</li><li>Correlate events across multiple systems to proactively surface and resolve deep, underlying issues.</li></ul> Requirements: <ul><li>Diploma/Degree in engineering/Computer Science / IT/Cyber Security from a recognized education institution</li><li>Professional qualification in information security, such as CISSP / CISM / CEH, or data Security product certifications will be advantageous.</li><li>9 to 12 years relevant experience</li><li>Strong working knowledge on Oracle Identity Governance 12c, Oracle Database, WebLogic, BI Publisher, Oracle Connectors, Linux, Unix &amp; Windows Enterprise Server OS, with mixed skills around administration, performance tuning and troubleshooting</li><li>Working knowledge of Python, java, Java Scripts,</li><li>Knowledge in network infrastructure like Load balancers, Firewalls, SSL etc</li><li>Working Knowledge on Directory - LDAP and AD Databases</li><li>Strong knowledge of Oracle SQL and proficient in writing complex SQL queries with hands on experience with reporting tools along with excellent computational ability.</li><li>Strong understanding of cybersecurity principles and frameworks including ISO 27001 &amp; NIST Cybersecurity Framework;</li></ul>

Responsibilities: Database Maintenance &amp; Support <ul><li>Assist in the maintenance of relational databases (Oracle, SQL Server).</li><li>Support schema creation, updates, normalization, and performance tuning.</li><li>Monitor data quality, identify inconsistencies, and help ensure data integrity across systems.</li></ul> Data Migration &amp; Platform Transition <ul><li>Support data extraction, transformation, and loading (ETL) during system migrations and platform upgrades.</li><li>Assist in transitioning data between legacy environments and modern systems, including Databricks.</li><li>Validate migrated data and document reconciliation results. Data Analysis &amp; Querying</li><li>Write and execute SQL queries for analysis, verification, and operational needs in Oracle and SQL Server environments.</li><li>Participate in exploratory and diagnostic analysis to uncover trends and support business decisions.</li></ul> Documentation &amp; Governance <ul><li>Maintain accurate documentation of data processes, transformations, and system behaviors.</li><li>Support compliance with organizational standards for data governance and metadata management.</li></ul> Requirements: Required Skills &amp; Qualifications <ul><li>Bachelor’s degree in Computer Science, Data Analytics, Information Systems, Engineering, or related field.</li><li>Foundational understanding of relational database concepts and SQL.</li><li>Introductory experience or coursework using Oracle, SQL Server, or similar RDBMS platforms.</li><li>Strong analytical thinking, attention to detail, and problem solving skills.</li><li>Ability to collaborate with technical teams in a fast paced environment.</li></ul> Preferred Skills &amp; Qualifications <ul><li>Exposure to Databricks or other big data / cloud analytics technologies.</li><li>Understanding of ETL concepts, data pipelines, or data transformation frameworks.</li><li>Familiarity with PL/SQL, SSIS, or other database programming tools.</li><li>Interest in learning modern data lake, delta, or virtualization technologies (e.g., Denodo).</li></ul>

Responsibilities: <ul><li>Build comprehensive firmware verification plans for various firmware features.</li><li>Develop white/ grey-box, known, and closed system testing methods to verify and validate firmware products.</li><li>Analyze failures from weekly regressions and perform root-cause analysis, requiring deep SSD domain expertise.</li><li>Manage test development, test deployment, test automation, and reporting activities.</li><li>Communicate challenges, solutions, and mitigation plans to cross-functional teams and management with clear and effective communication of both technical and non-technical topics.</li><li>Participate in code reviews and guide the team to ensure comprehensive coverage and accurate architectural build.</li><li>Establish strong working relationships with firmware development engineers to improve code quality.</li><li>Lead a team of technical people, as required.</li></ul>&nbsp;Requirements: <ul><li>B.Sc. in Electrical Engineering, Computer Engineering, or Computer Science</li><li>6-8 years of pertinent experience in SSD firmware test development</li><li>Comprehensive understanding and substantial experience in SSD firmware testing and Python programming</li><li>Deep understanding of storage industry protocols such as PCIe, NVMe and NVMe-MI, with ability to design and develop tests aligned with specifications.</li><li>Familiarity with Agile/ Scrum development, GIT-based development workflow and branch management.</li><li>Experience with automated build, continuous integration, and test automation systems</li><li>Highly organized, creative, motivated, and passionate about achieving results</li><li>Ability to work on complex tasks independently with minimal supervision</li><li>Demonstrated leadership abilities and the capability to mentor less experienced engineers</li><li>Excellent problem-solving and analytical skills</li><li>Strong interpersonal and communication skills, and a great teammate</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: <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>

Responsibilities: <ul><li>Develop and implement 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>Develop 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>Education: Master’s degree or above in a quantitative or technical field (Statistics, Computer Science, Mathematics, Data Science, etc.).</li><li>Strong experience in machine learning, NLP, and LLM-based modeling.</li><li>Strong 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>Strong foundation in statistics, modeling, and large-scale text processing.</li></ul>

Responsibilities: Data Infrastructure:&nbsp; <ul><li>Prepares data infrastructure to support the efficient storage and retrieval of data.</li></ul> Data Formats:&nbsp; <ul><li>Examines and resolves appropriate data formats to improve data usability and accessibility across the organization.</li></ul> Data &amp; Analytical Solutions:&nbsp;&nbsp; <ul><li>Develops complex data products and solutions using advanced engineering and cloud based technologies, ensuring they are designed and built to be scalable, sustainable and robust.</li></ul> Data Pipelines:&nbsp;&nbsp; <ul><li>Develops and maintains streaming and batch data pipelines that facilitate the seamless ingestion of data from various data sources, transform the data into information and move to data stores like data lake, data warehouse and others.</li></ul> Data Systems:&nbsp;&nbsp; <ul><li>Reviews existing data systems and architectures to identify areas for improvement and optimization.</li></ul> Stakeholder Management: <ul><li>Collaborates with multi-functional data and advanced analytic teams as well as with business teams to gain requirements and ensure that data solutions meet the functional and non-functional needs of various partners.</li></ul> Data Frameworks:&nbsp; <ul><li>Builds complex prototypes to test new concepts and implements data engineering frameworks and architectures that improve data processing capabilities and support advanced analytics initiatives.</li></ul> Automated Deployment Pipelines:&nbsp;&nbsp; <ul><li>Develops automated deployment pipelines improving efficiency of code deployments with fit for purpose governance.</li></ul> Data Modeling:&nbsp;&nbsp; <ul><li>Performs complex data modeling in accordance to the datastore technology to ensure sustainable performance and accessibility.</li></ul> Requirements: <ul><li>Minimum requirement of 4 years of relevant work experience.&nbsp;</li><li>Typically reflects 5 years or more of relevant experience.</li></ul>

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43 python Jobs found

Forward Deployed AI Strategist

Senior Production Support Engineer – IDM Engineering (VP2)

Data Analyst

Principal/Staff, Firmware and Product Test (SSD)

Senior Software Engineer AI

Software Engineer AI

Manager, Data Science - Agentic AI

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Senior Data Engineer

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43 python Jobs found

Forward Deployed AI Strategist

Senior Production Support Engineer – IDM Engineering (VP2)

Data Analyst

Principal/Staff, Firmware and Product Test (SSD)

Senior Software Engineer AI

Software Engineer AI

Manager, Data Science - Agentic AI

Senior Data Scientist III - Agentic AI

Senior Data Scientist II - Agentic AI

Senior Data Engineer

WhiteCrow WhiteCrow is on a mission to connect companies with the best talent across the globe.

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