AI Tech Lead (Data Engineering)_D3006

Role overview

AI Tech Lead (Data Engineering)_D3006 at Allianz

Purpose of the Role.

Responsibilities

• You will own the technical direction of AI projects, lead a team of AI Engineers, and serve as the bridge between business stakeholders, solution architects, and engineering teams.
• Lead AI projects through a stage-gated delivery model: Ideation → Framing → Design → Build → Test → UAT → Production.
• Manage non-functional requirements (latency, cost-per-task, throughput) and ensure they are met at each gate.
• Drive parallel workstreams (e.g., systems data readiness alongside agent build) to prevent schedule slip.
• Coordinate cross-team dependencies with platform, MLOps, data, and business teams.
• Lead, mentor, and grow a team of AI Engineers across agent development, prompt engineering, and LLM integration.
• Manage team capacity, sprint planning, and delivery commitments.
• Lead prompt engineering strategy including system prompt design, few-shot patterns, chain-of-thought reasoning, and prompt versioning.
• Drive evaluation harness design: golden-set creation, grading rubrics, pass-bar thresholds, and CI-integrated eval suites.
• Ensure non-determinism is managed through stable eval scores across consecutive runs.
• Ensure all AI solutions follow zero-trust security principles: managed identities, no secrets in code, defence in depth.
• Design and enforce guardrails for agent actions including blast-radius assessment and fallback paths.
• Contribute to governance frameworks including model cards, explainability documentation, and audit evidence.
• Collaborate with business SMEs on use-case framing, autonomy-level decisions, and acceptance criteria.
• Drive token usage monitoring, cost optimisation, and model-tier selection strategies.

Required qualifications

• Required Skills & Experience.
• Essential. 8+ years in software engineering with at least 3 years focused on AI/ML solutions. 2+ years of hands-on experience with Large Language Models (GPT-4 class or equivalent) in production environments.

Employment details

• Location: India, PUNE [India]

Benefits

• Insurance, financial services, or other regulated-industry experience.
• Allianz Group is one of the most trusted insurance and asset management companies in the world.

Additional role details

• The AI Lead is a senior technical leadership role responsible for driving the end-to-end delivery of AI and Agentic AI solutions.
• You are accountable for solution quality, delivery cadence, and production readiness of AI workloads.
• Key Accountabilities.
• Technical Leadership & Architecture.
• Own the technical delivery of AI solutions from ideation through to production deployment.
• Define and enforce solution architecture patterns including single-agent, multi-agent, and orchestration topologies.
• Make technology selection decisions with cost, performance, and maintainability trade-offs.
• Design and approve prompt architectures, retrieval strategies, and context assembly patterns.
• Establish reference architectures and reusable design patterns for the AI engineering team.
• Delivery Management.
• Own design approval gates and ensure every deliverable meets agreed quality bars before stage exit.
• Team Leadership.
• Conduct code reviews and AI engineering quality checks.
• Establish and enforce development standards, coding guidelines, and engineering best practices.
• Foster a culture of experimentation, continuous learning, and knowledge sharing.
• Agentic AI & LLM Expertise.
• Design and oversee agentic orchestration solutions (multi-agent systems, state management, human-in-the-loop patterns).
• Architect Retrieval-Augmented Generation (RAG) pipelines including chunking strategies, embedding models, and retrieval quality evaluation.
• Security & Governance.
• Integrate content safety checks on all LLM inputs and outputs.
• Own adversarial testing strategy: prompt injection, jailbreak, and tool-misuse test packs.
• Stakeholder Engagement.
• Translate business requirements into feasible AI solution designs.
• Present architecture decisions, PoC findings, and delivery progress to senior stakeholders.
• Participate in joint go/no-go gates for production deployment.
• Observability & Operations.
• Define observability and trace design requirements for AI workloads (logging, telemetry, cost tracking).
• Establish alert thresholds, on-call procedures, and hypercare plans for production AI systems.
• Own post-deployment monitoring, prompt optimisation, and continuous improvement cycles.
• Proven experience designing and delivering agentic AI systems (multi-agent orchestration, tool-calling, state management).
• Strong proficiency in Python and modern AI frameworks (LangChain, LangGraph, Semantic Kernel, or equivalent).
• Deep understanding of prompt engineering: system prompts, context assembly, retrieval strategies, and evaluation methods.
• Experience with RAG architectures: vector databases, embedding models, chunking strategies, retrieval quality metrics.
• Hands-on experience with cloud AI platforms (Azure AI, AWS Bedrock, GCP Vertex AI, or equivalent).
• Experience leading engineering teams (2–6 direct reports) with a track record of delivering production AI systems.
• Strong understanding of CI/CD for AI workloads including eval-suite integration and automated testing.
• Knowledge of identity and security patterns: managed identities, RBAC, content safety, zero-trust principles.
• Desirable.
• Experience with event-driven architectures (Kafka, Service Bus, or equivalent messaging systems).
• Familiarity with ML model serving and MLOps (MLflow, model registries, drift detection).
• Experience with OCR / Document Intelligence solutions.
• Knowledge of FinOps practices for AI workloads (token cost tracking, model-tier optimisation, budget governance).
• Experience with rules engines (Drools, or equivalent).
• Familiarity with Infrastructure-as-Code (Terraform, Bicep, or equivalent).
• Key Competencies.
• Technical Depth.
• Can go deep on LLM internals, agent orchestration, and system design while maintaining a broad architectural view.
• Delivery Focus.
• Drives outcomes through structured delivery with clear gates, quality bars, and accountability.
• Communication.
• Translates complex AI concepts for business audiences; writes clear design documents and architecture decision records.
• Pragmatism.
• Balances innovation with production readiness; knows when to PoC and when to ship.
• Security Mindset.
• Treats security as non-negotiable; designs with defence in depth from day one.
• People Leadership.
• Grows engineers through mentoring, code review, and creating space for experimentation.
• Collaboration.
• Works effectively across business, data, platform, and operations teams with a joint-accountability mindset.
• What Success Looks Like (First 12 Months).
• Delivered 2–3 AI/agentic solutions to production with measurable business impact.
• Established engineering standards, templates, and accelerators adopted by the wider team.
• Built and maintained an evaluation framework with CI-integrated golden-set testing.
• Achieved stable production operations with defined SLAs, observability, and incident response.
• Grown the AI engineering team's capability through mentoring, knowledge sharing, and structured onboarding.
• Contributed to cross-cutting frameworks (security, observability, governance) used across the organisation.
• Caring for our employees, their ambitions, dreams and challenges, is what makes us a unique employer.
• Together we can build an environment where everyone feels empowered and has the confidence to explore, to grow and to shape a better future for our customers and the world around us.
• At Allianz, we stand for unity: we believe that a united world is a more prosperous world, and we are dedicated to consistently advocating for equal opportunities for all.
• And the foundation for this is our inclusive workplace, where people and performance both matter, and nurtures a culture grounded in integrity, fairness, inclusion and trust.
• We therefore welcome applications regardless of ethnicity or cultural background, age, gender, nationality, religion, social class, disability or sexual orientation, or any other characteristics protected under applicable local laws and regulations.
• Great to have you on board.
• Let's care for tomorrow.