Sr Enterprise Solutions Applied AI Engineer

Overview

Own end-to-end delivery of complex AI services and Generative AI features that automate or augment enterprise workflows, combining software engineering execution with multi-step agent design and production operations.

What you'll do

• Own the development of a complex AI service or GenAI feature from concept through production rollout and ongoing iteration.
• Translate ambiguous business requirements into user stories, acceptance criteria, and technical implementation plans.
• Integrate agentic solutions with enterprise systems (e.g., CRMs, ERPs, HR platforms, data warehouses, internal APIs) and ensure production-grade performance through rapid iteration and troubleshooting.
• Lead pilot launches and transitions, including documentation, user enablement, and stakeholder alignment.
• Lead the design and implementation of multi-step agents, including tool/function calling, retrieval, state management, and human-in-the-loop oversight where required.
• Develop evaluation approaches (test suites, golden datasets, regression checks) and optimize solutions for accuracy, latency, reliability, and cost.
• Implement production observability (logging, tracing, monitoring) and contribute to runbooks and incident response processes for AI services.
• Extract successful patterns from delivery work to create reusable libraries, templates, and reference implementations for other teams.
• Lead technical reviews and share best practices for secure, reliable, and user-trustworthy agentic systems.
• Mentor and coach P1-P2 engineers through code reviews, design reviews, and day-to-day execution.

What you'll need

• 8+ years of experience in software engineering, including ownership of production services.
• 3+ years building and deploying AI/ML or Generative AI solutions that deliver measurable business results in production.
• Strong proficiency with LLM application patterns: prompt engineering, Retrieval-Augmented Generation (RAG), and tool/function calling within agentic systems.
• Experience with agent frameworks (e.g., LangChain, LlamaIndex, Semantic Kernel, Microsoft Agent Framework, or similar).
• Hands-on experience with enterprise integrations, authentication/authorization, and secure API design.
• Operational excellence: familiarity with logging, tracing, monitoring, performance tuning, and cost management for AI applications.
• Strong communication skills and demonstrated ability to lead cross-functional delivery with business and technical stakeholders.
• Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).

Details

• Hybrid role.
• Location: Bangalore, India.