Job Title

Position Name: Lead Generative AI EngineerPosition DescriptionThe Lead Generative AI Engineer is the organization’s senior technical authority for designing, building, and operating enterprise-grade generative AI systems. The role leads a small, high-impact Generative AI engineering team in Pune responsible for developing and supporting production AI services used across multiple internal products and workflows, while serving as the technical lead for the organization’s enterprise Generative AI platform.This leader architects and oversees the full lifecycle of production generative AI and agentic systems from initial design through deployment, optimization, and governance. The team owns the development, deployment, and operational support of these systems in production, ensuring solutions integrate with enterprise data and services and meet strict standards for reliability, observability, security, and compliance.Working closely with data, platform, security, and U.S.-based engineering teams, the Lead Generative AI Engineer establishes technical standards and best practices for AI architecture, including agent orchestration, retrieval-augmented generation pipelines, structured outputs, and human-in-the-loop controls. The role also drives continuous improvement through monitoring, evaluation frameworks, and performance optimization to manage cost, latency, and scale while enabling responsible, enterprise-grade AI capabilities across the organization.The ideal candidate brings curiosity, enthusiasm, and a can-do attitude, with a passion for learning emerging AI technologies and solving complex problems in production environments.Work Location & Schedule ExpectationsThis role works closely with U.S.-based engineering leadership while leading a small AI engineering team located in Pune.Hybrid: Minimum 3 days per week in the office, coordinated with the team to ensure shared in-person working days.US Collaboration: Daily schedule must include 3–4 hours overlap with U.S. Eastern Time (EST) to support collaboration with U.S.-based engineering and product teams.Deployment Support: Ability to occasionally work outside normal hours (early mornings, evenings, weekends) for deployments or incidents.Operational Responsibility: Availability during critical releases or production events to maintain system reliability.Core AttributesEmbraces an iterative mindset; delivering value frequently while refining solutions based on feedback.Curiosity, enthusiasm, and a can-do attitude.Demonstrates patience, professionalism, and active listening, fostering collaboration and understanding across diverse, distributed teamsPassion for learning emerging AI technologies and solving complex production problems.Clearly conveys ideas in both spoken and written form, tailoring messages for diverse audiences, and presents complex technical concepts in a concise, understandable mannerQualifications & ExperienceRequired ExperienceBachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field (or equivalent practical experience).7+ years of software engineering experience, including designing and operating complex distributed systems in enterprise environments.3+ years building cloud-native APIs and microservices for production environments, with experience in performance, scaling, and reliability.1+ years designing event-driven and service-oriented architectures on Microsoft Azure, including services such as App Service, Functions, Service Bus, and Blob Storage.1+ years building and operating production AI/ML or LLM systems, including experience evaluating model outputs and implementing testing or validation frameworks.Proven ability to influence architecture decisions, establish technical standards, and drive engineering best practices across teams.Preferred ExperienceMaster’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.3+ years designing and operating agentic AI systems and RAG architectures in production environments.Experience implementing vector search or semantic retrieval systems using embeddings and vector databases.Experience implementing governance, human-in-the-loop controls, and compliance frameworks for enterprise AI deployments.Experience developing automated evaluation or testing frameworks for AI or LLM outputs.Experience monitoring and operating AI systems at scale, including observability, alerting, and reliability improvements.Familiarity with AI governance, enterprise compliance frameworks, or responsible AI practices.Knowledge of regulatory or ethical considerations related to AI systems.Experience with Python frameworks commonly used in AI services, such as FastAPI, asyncio, and Pydantic.Experience deploying containerized applications using Docker or similar technologies.Required Technology Stack KnowledgeAzure App Service, Azure Functions, Service BusAzure Blob Storage, Azure Key Vault, Azure RBACAzure OpenAI Service, Azure AI Document IntelligenceMicrosoft AI Foundry / Azure AI StudioAzure Application InsightsInfrastructure as Code with BicepKey Duties and ResponsibilitiesAI Architecture & LeadershipServe as the technical authority for enterprise Generative AI architecture and engineering standards.Lead the design, implementation, and operation of production-grade AI systems, including agentic and multi-step workflows, RAG pipelines, and LLM-powered applications.Establish deterministic, versioned, and observable patterns for AI workflows across enterprise production environments.Remain hands-on in building and optimizing core AI platform components, continuously evaluating emerging AI models, tools, and architectural approaches.Integrate AI systems with enterprise data, APIs, and platforms to enable mission-critical workflows.Reliability, Performance & OperationsEnsure AI systems meet enterprise standards for reliability, scalability, latency, throughput, and cost efficiency.Implement monitoring, observability, tracing, alerting, and evaluation frameworks to maintain operational visibility and rapid issue resolution.Design and maintain CI/CD pipelines for deployment, versioning, and release management of AI services.Lead production support, incident response, and root cause analysis for AI systems in live environments.Governance, Security & Responsible AIImplement human-in-the-loop (HITL) controls, feedback mechanisms, and evaluation pipelines to ensure trusted and auditable AI outputs.Secure AI systems against prompt injection, data leakage, unauthorized access, and other vulnerabilities, aligning with enterprise compliance standards.Define and enforce structured outputs, schema validation, and operational safeguards to protect sensitive data.Team Leadership & Cross-Functional CollaborationProvide technical leadership, mentorship, and coordination for the India-based AI engineering team.Collaborate with US-based engineering, product, data, and security teams to design resilient, compliant, and high-impact AI solutions.Advise leadership on enterprise AI capabilities, architectural decisions, and emerging technologies.Partner with stakeholders to define SLAs, SLOs, and performance targets for production AI services.Equal Employment OpportunityWe are committed to building a diverse workforce and providing equal employment opportunities to all qualified candidates. All hiring decisions are based on qualifications, skills, and business needs, without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, age, national origin, disability, or any other status protected by applicable law.