Essential Skills

• AI/ML Testing Knowledge
• Data Validation & Testing
• Proficiency in automation using Python/Java
• SQL & Data Handling
• Understanding of performance testing tools (JMeter, Locust) especially for AI systems handling large-scale data.

Key Responsibilities

Skills Required

• 6 – 10 years of product management experience, with ownership of customer-facing platforms or APIs.
• 3+ years shipping and operating AI/ML-powered products in production.
• Strong understanding of LLM-based systems, RAG architectures, and AI ecosystem.
• Knowledge of Agent development frameworks and MCP.
• Ability to reason about trade-offs between accuracy, latency, cost, and UX.
• Comfortable reviewing prompts, experiments, dashboards, and system metrics.
• Strong communication skills in highly technical and ambiguous domains.

Nice to Have

• Experience with semantic technologies such as knowledge graphs, ontologies, or semantic data models.
• Experience building AI platforms for enterprise customers.
• Familiarity with AI governance, compliance, or regulated environments.
• Exposure to UX patterns for AI-driven workflows.

Key Responsibilities

• Own the vision, roadmap, and success metrics for the AI platform.
• Define core platform capabilities.
• Enable customer and internal teams to build AI use cases using scalable platform primitives.
• Prototype AI workflows and reference implementations to validate new capabilities.
• Define and track KPIs for AI quality, latency, reliability, cost, and adoption.
• Embed enterprise-grade guardrails for security, privacy, and safe AI usage.
• Influence (not solely own) decisions e.g. model selection, buy vs build, risk trade-offs, etc
• Act as the product interface across engineering, ML, security and go-to-market teams.

Skills Required

• 10-15 years of experience in data management, with at least 10 years in a similar role.
• Proven experience leading teams and projects in data management.
• Strong proficiency in big data technologies (e.g., Spark, Kafka), SQL, and data warehousing solutions.
• Experience with ETL and ELT tools and processes.
• Proficiency in data modelling and data warehouse / data lake / data lakehouse concepts.
• Knowledge and experience of data quality concepts and metadata management.
• Understanding of data governance principles and best practices, like GDPR and HIPAA.
• Good understanding of product lifecycle and roadmap planning
• Experience with large product or services companies is preferred.

Roles & Responsibilities

Key Responsibilities

• Drive and deliver the design, development, and deployment of our data management and storage related modules in mcube.
• Oversee data architecture and data integration processes across modules.
• Enablement of real-time and batch ETL and ELT processes, ensuring data quality, performance and optimal usage of appropriate storage technologies.
• Ensure the platform’ data management and storage modules enable our customers to follow their data governance principles and best practices, including authorization, logging and data security.
• Ensure the platform has consistent and secure data access controls, data masking, and encryption processes.
• Establish and develop/integrate a central technical and business meta data layer leveraging modern, knowledge graph and AI based technologies
• Lead a team of developers to deliver above capabilities and features in a matrix environment
• Partner with product management to ensure alignment with market and customer trends.
• Partner with QA to deliver industry standard software quality

Other Information

• Bachelor’s or Master’s degree in Computer Science or a related field (BTech preferred).

Skills Required

• Expert knowledge of data science algorithms, methodologies, and end-to-end lifecycle (AI/ML/GenAI), MLOps and post deployment service of AI models
• Strong comprehension of complex Oil & Gas and downstream Petrochemical industries problem.
• Exceptional articulation skills to communicate technical concepts clearly to both technical and business stakeholders.
• Advanced analytical skills for strategic problem-solving and actionable insight generation.

• Exposure to cloud platforms (AWS/Azure/GCP), DevOps, deployment and scaling frameworks
• Experience in leading agile teams and agile methodology.
• Familiarity with data visualization tools (e.g., Tableau, Power BI).
• Understanding of data engineering principles and big data.

Roles & Responsibilities

• Lead data science efforts (AI, ML, GenAI, optimization) for multiple client engagements in n Oil & Gas and downstream Petrochemical industries.
• Manage end-to-end Data Science project lifecycle from problem comprehension, analytical solution development to final delivery.
• Act as primary point of contact for client interactions, presentations, and requirement elicitation.
• Guide teams on advanced data science techniques ensuring alignment with business objectives.
• Collaborate cross-functionally with domain experts, business stakeholders, and technical teams to deliver robust analytical solutions.

Other Information

Skills Required

• Work closely with stakeholders to identify business needs and requirements.
• Document and analyze existing insurance processes, workflows, and systems.
• Identify gaps and recommend solutions to improve efficiency, customer experience, and compliance.

• Strong analytical and problem-solving abilities.
• Proficient in business analysis tools and techniques.
• Excellent communication and stakeholder management skills.
• Experience working in the Oil & Gas industry will be preferred.
• Understanding of Oil & Gas business processes, workflows, and domain-specific applications will be an added advantage.

• Act as a liaison between business teams, IT, and support vendors during the project lifecycle.
• Monitor project progress and ensure alignment with business objectives.

• Analyze claims, underwriting, policy, and customer data to identify trends and opportunities.
• Develop dashboards and reports to support decision-making and strategy formulation.
• Ensure business rules align with regulatory requirements and industry standards.
• Assist in project risk analysis and the development of mitigation strategies.
• Candidates with prior experience in the Oil & Gas domain will be preferred.

Other Information

Roles & Responsibilities

• Oversee and coordinate software releases across multiple development streams and applications.
• Plan and manage monthly and ad hoc releases.
• Collaborate with cross-functional teams to define release scope, timelines, and deliverables.
• Ensure timely delivery of high-quality software updates and releases.
• Act as the primary point of contact for all release-related activities.
• Provide regular status updates to stakeholders and leadership teams.
• Facilitate release reviews, retrospectives, and continuous improvement initiatives.
• Identify opportunities for process improvement and implement best practices.
• Ensure compliance with organizational standards, policies, and procedures.
• Apply strong project management, communication, and coordination skills to manage release activities effectively.
• Prior experience working in the Oil & Gas industry is mandatory/preferred.
• Understanding of Oil & Gas domain processes, applications, and business workflows will be an addedadvantage.