Staff Engineer, Product Software

Overview

Drive the development and delivery of next-generation AI-powered platforms and customer-facing agentic solutions. Lead the design and implementation of scalable, secure, and reliable AI solutions using LLMs, Agentic AI, RAG, MCP, and modern cloud-native development practices.

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 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 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.
• Monitor and analyze user feedback to drive continuous improvement in applications.

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.
• Strong customer-first mindset with a focus on platform usability and adoption.
• Ability to thrive in fast-paced, ambiguous environments.

Details

• Location: Bangalore Office BLS2.