Overview
Lead hands-on engineering for AI-powered platforms and customer-facing agentic solutions, combining software engineering with expertise in LLMs, Agentic AI, RAG, MCP and cloud-native development.
What you'll do
- Design, build, deploy, and maintain LLM-powered agents and AI-driven applications
- Integrate AI capabilities into existing software platforms to enhance functionality, automation, and user experience
- Implement tool integration using Model Context Protocol (MCP) and agent-to-agent (A2A) communication patterns
- Design and implement automated evaluation frameworks, quality gates, benchmarking processes, and release criteria for customer-facing AI agents
- Establish guardrails, human-in-the-loop approval mechanisms, escalation workflows, and Responsible AI governance controls
- Monitor and optimize agent quality, accuracy, latency, reliability, adoption, observability, and operational costs
- Design, implement, and maintain Retrieval-Augmented Generation (RAG) architectures, vector databases, and knowledge engineering solutions
- Develop AI-enabled APIs and backend services using technologies such as Python, FastAPI, containerized services, and REST-based integration patterns
- Troubleshoot agent failures and continuously improve agent performance through prompt engineering, context optimization, workflow orchestration, and evaluation feedback loops
- Design, build, and manage automated CI/CD pipelines using GitHub Actions (GHA) and modern DevOps practices
- Collaborate with cross-functional teams to gather requirements, define technical solutions, and deliver exceptional customer experiences
- Troubleshoot and resolve issues related to client interfaces, APIs, integrations, and end-user interactions
- Provide hands-on leadership in software architecture, design, development, automation testing, deployment, and operational support
- Drive architecture decisions and establish engineering standards for AI-powered platforms and services
- Partner with product managers, architects, security teams, and engineering leaders to define technical strategy and execution plans
- Evaluate emerging AI technologies, frameworks, tools, and industry best practices to drive innovation and continuous improvement
- Provide technical estimates, identify risks, and contribute to roadmap planning, prioritization, and delivery execution
What you'll need
- Bachelor's degree in computer science, Software Engineering, Data Science
- 6+ years of experience in the full software development life cycle, including coding standards, code reviews, version control, build processes, and testing
- 6+ years of experience in software design, development, and algorithm related solutions
- 5+ years of programming with Python or Java languages
- 3+ years of experience in developing, deploying or optimizing ML models
- 3+ years of hands-on experience building LLM-powered applications, AI assistants, or autonomous agent systems
- Experience with prompt engineering, context engineering, tool calling, retrieval systems, and multi-agent workflows
- Solid experience designing APIs, microservices, distributed systems, and event-driven architectures
- Experience with agent frameworks and orchestration technologies such as LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar
- Experience working with MCP (Model Context Protocol), Agent-to-Agent (A2A) communication, and tool orchestration frameworks
- Experience with Anthropic, OpenAI, Azure OpenAI, Amazon Bedrock, Vertex AI, or similar AI platforms
- Knowledge-engineering experience including vector databases, embeddings, hybrid search, retrieval systems, and enterprise knowledge graphs
- Experience implementing AI observability, tracing, evaluation platforms, and cost optimization solutions
- Experience implementing automated testing, CI/CD pipelines, observability, and operational monitoring
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform
- Experience in REST-based API development, API lifecycle management and/or client SDKs development
- Strong written and verbal communication skills, with the ability to explain complex concepts to non-technical stakeholders
- Self-motivated, with a passion for learning and staying up-to-date with the latest technologies in the field
- Ability to work independently and as part of a team, managing multiple tasks and projects simultaneously
- Monitor and analyze user feedback to drive continuous improvement in our applications
- Strong customer-first mindset with a focus on platform usability and adoption
- Ability to thrive in fast-paced, ambiguous environments
Details
- Location: Bangalore Office
- This posting is for a backfill position
Read the full description and apply on the company’s own careers page.