Lead AI Engineer
Pune · Director
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First 72 hours
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Job description
Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!
- Design, develop, and deploy AI/GenAI applications, RAG pipelines, and intelligent workflow automation
- Build backend services, APIs, integrations, and orchestration frameworks using LLMs, model APIs, and enterprise data.
- Develop AI-powered knowledge assistants, workflow automation, and decision support solutions.
- Leverage AI-assisted development while ensuring code quality, security, reliability, observability, and governance.
- Define evaluation frameworks to measure AI quality, accuracy, latency, and system performance.
- Collaborate with business, IT, Security, Data, HR, and Finance teams to identify and deliver high-value AI use cases.
- Prototype rapidly and scale solutions into secure, production-ready deployments.
- Optimize AI solutions for performance, scalability, reliability, and cost.
- Develop reusable AI components, frameworks, and best practices to accelerate enterprise adoption.
- 7–12+ years of experience in Software Engineering, AI/ML, or GenAI application development.
- Proven experience building and deploying production-grade AI/GenAI solutions.
- Strong expertise in Python, backend development, APIs, system integration, and workflow orchestration.
- Hands-on experience with RAG, LLMs, prompt engineering, tool/agent calling, AI evaluation, and observability.
- Experience integrating enterprise applications, data platforms, and services using APIs and event-driven architectures.
- Strong analytical, systems thinking, and problem-solving skills with the ability to translate ambiguous business problems into scalable AI solutions.
Preferred Qualifications
Experience with vector databases, embeddings, semantic search, and advanced RAG architectures.
- Knowledge of SQL, data engineering, and data pipelines.
- Experience integrating AI into enterprise applications and business workflows.
- Exposure to intelligent agents, automation platforms, and AI governance frameworks.
- Experience building reusable AI frameworks, accelerators, or enterprise AI platforms.
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