Senior Manager - Tech Consulting - FS - CNS - TC - Technology Strategy & Transformation - Pune

JD for Agentic AI Lead

Digital Engineering Opportunity in Modern Technology Platforms 

Step into the Digital Engineering Studio, where bold ideas, data, and intelligent automation come together to redefine the future of insurance. This is a high‑energy environment for young technologists who are eager to learn, build, and innovate at scale. You’ll work across project governance, UI/UX engineering, API development, and modern web and mobile platforms, creating intuitive portals for self‑buying health insurance, policy renewal, and claims tracking. Every solution you build—whether customer‑facing or agent‑enabled—will have real‑world impact, shaping seamless digital journeys for millions. 

For aspiring Data Engineers and AI enthusiasts, this role adds an exciting edge. You’ll design and power data pipelines that fuel RAG (Retrieval‑Augmented Generation) solutions, enable intelligent search, and support AI‑driven decisioning across Insurance Digital platforms. With access to AI‑powered coding assistants and agentic development tools, you’ll accelerate development while learning best‑in‑class engineering practices. From leading Core Policy Admin System integrations to connecting with government ecosystems like ONDC, PMBY, and SARTHI, you’ll gain hands‑on exposure to large‑scale, mission‑critical systems—perfect for those who want to grow fast, experiment fearlessly, and build the digital backbone of tomorrow’s insurance landscape. 

Job Description:  

We are seeking an Agentic AI Lead with strong hands-on and strategic expertise in architecting and delivering intelligent, autonomous, and AI-enabled applications at enterprise scale, leveraging modern agentic and GenAI frameworks, cloud-native platforms, and scalable backend architectures. The role requires deep experience leading the design and development of robust backend and platform services, integrating enterprise APIs and diverse data sources, working with relational databases such as PostgreSQL, and deploying production-grade systems on Google Cloud Platform (GCP) using mature CI/CD pipelines. The ideal candidate is a customer- and business-centric technology leader who can translate complex requirements into secure, resilient, and high-quality agentic solutions supporting web, mobile, and enterprise workflows, while setting architectural direction, enforcing engineering excellence, and guiding teams on advanced agent orchestration patterns, DevOps/MLOps best practices, and reliable delivery of impactful AI-driven digital solutions.

Candidate should have experience of Leveraging AI‑assisted development tools (e.g., code generation, code reviews, debugging assistants) to improve coding speed, quality, and developer productivity. Demonstrate openness to adopting AI‑based tools and workflows to accelerate development while adhering to coding standards and best practices.  

Understanding of the general insurance domain is good to have. 

Location: Pune – Work from Office 

Notice Period: Up to 2 Months. 

1. Agentic AI Lead – 8+ Years 

Roles & Responsibilities

• Provide enterprise-wide technical and strategic leadership for the vision, architecture, and execution of large-scale agentic AI platforms and solutions across multiple business lines and domains.
• Own the agentic AI technology roadmap, guiding long-term evolution of agent architectures, platforms, accelerators, and operating models aligned with business and industry strategy.
• Lead the design and governance of complex, distributed agentic systems, including multi-agent ecosystems, cross-domain orchestration, long-running autonomous workflows, and human-in-the-loop decision systems.
• Set architectural guardrails and engineering standards for agent design, orchestration, memory, state management, reasoning, planning, and failure recovery at enterprise scale.
• Act as the highest level of technical authority on agent behaviour and intelligence, taking oversight and accountability for reasoning strategies, planning algorithms, escalation logic, risk handling, and system trustworthiness.
• Architect highly composable AI systems that integrate LLMs, traditional ML models, enterprise tools, APIs, event-driven systems, data platforms, and cloud-native services into cohesive intelligent workflows.
• Drive large-scale enterprise integration, enabling agentic platforms to work seamlessly with legacy systems, core business applications, data ecosystems, and partner platforms.
• Define and institutionalize enterprise reference architectures, design patterns, reusable IP, accelerators, and engineering playbooks for agentic AI adoption.
• Champion Responsible AI at an enterprise level, embedding governance, explainability, risk controls, auditability, privacy, security, and regulatory compliance across platforms and solutions.
• Partner with executive stakeholders, business leaders, and enterprise architects to shape AI-driven business transformation, translating strategic objectives into scalable agentic capabilities.
• Oversee system performance and economics, driving optimization across quality, accuracy, latency, throughput, reliability, and cost at portfolio scale.
• Provide executive oversight for production operations, including incident management, systemic risk mitigation, platform resilience, and SLA adherence across mission-critical deployments.
• Build and lead high-performing agentic engineering teams, mentoring senior technologists, principal engineers, and architects, and setting a culture of technical excellence and innovation.
• Drive innovation, thought leadership, and external visibility, contributing to internal IP, accelerators, whitepapers, patents, conferences, and client-facing AI transformation initiatives.

Education

• BE / B.Tech in Computer Science, Engineering, or a related discipline
• Postgraduate qualification (M.Tech / MS / MBA – preferred)

Required Experience & Technical Skills

• 14–18 years of overall experience in advanced software engineering and AI systems, including leading AI, GenAI, or autonomous agent initiatives at enterprise scale.
• Proven track record in architecting and scaling agentic AI platforms across multiple domains, teams, and geographies.
• Deep expertise in multi-agent systems, autonomous decision-making, planning and reasoning architectures, human–agent collaboration, and enterprise workflow automation.
• Advanced hands-on and conceptual mastery of LLMs, prompt/program synthesis strategies, reasoning frameworks, evaluation methodologies, and continuous learning loops.
• Strong experience with agent frameworks and platforms (LangChain, LangGraph, AutoGen, CrewAI, etc.) with the ability to design custom enterprise-grade agent foundations beyond framework defaults.

• Expert-level understanding of agent orchestration, including hierarchical/task-based planning, tool invocation strategies, exception handling, resilience patterns, and agent collaboration protocols without over-dependence on LangChain/LangGraph-style abstractions. 

• Deep knowledge of memory, state, and context management, including short-term/long-term memory, vector databases, knowledge graphs, session isolation, and lifecycle governance.
• Advanced experience with RAG systems, search relevance optimization, grounding strategies, hallucination mitigation, and enterprise knowledge integration.
• Demonstrated algorithmic and model stewardship, including evaluation frameworks, risk modelling, bias analysis, and continuous optimization.
• Extensive experience deploying and operating AI platforms on Google Cloud Platform (GCP) using scalable, secure, and cost-efficient cloud-native architectures.
• Experience working with Postgre database.
• Strong leadership in MLOps and AI Platform Engineering, including CI/CD, model and prompt lifecycle management, testing at scale, and controlled enterprise releases.
• Expertise in AI observability and governance, including telemetry, tracing, quality evaluation frameworks, explainability dashboards, and cost governance.
• Strong command of AI security, privacy, and regulatory compliance, aligning with enterprise policies, industry regulations, and Responsible AI standards.
• Preferred: Deep exposure to General Insurance (Health, Motor, Travel) or other regulated industries, with experience driving AI-led transformation of core business processes.

Leadership & Behavioural Competencies:

• Demonstrates strategic thinking, executive presence, and systems-level problem solving in highly complex environments.
• Communicates with clarity and influence at senior leadership and C-suite levels, bridging business strategy and deep technology.
• Inspires and develops senior technical leaders, fostering innovation, accountability, and engineering excellence at scale.
• Exhibits strong professional integrity, decisiveness, and resilience in high-stakes, mission-critical AI initiatives.