Lead AI Engineer – Agentic Engineering

This is a fully remote position, open to applicants in India.

📋 Description

• Facilitate the implementation of Agentic Engineering methodologies throughout the software development lifecycle by utilizing AI agents to enhance and automate engineering workflows.

• Utilize Claude Code, Claude Code Skills, PI, Hermes Agent, and similar AI coding/engineering agents in everyday software development tasks.

• Create AI-supported workflows for requirements analysis, code generation, code comprehension, refactoring, testing, debugging, documentation, code review, and deployment.

• Design agent workflows capable of comprehending large codebases, managing context, employing tools, performing multi-step engineering tasks, and recovering from failures.

• Develop practices for context management, context engineering, tool invocation, agent orchestration, guardrails, human-in-the-loop workflows, and autonomous task execution.

• Design and execute assessments that measure agent accuracy, dependability, code quality, task completion, regression, and overall effectiveness.

• Analyze new agentic coding tools and methodologies to enhance engineering productivity and software quality.

• Architect and create production-ready multi-agent and agentic systems designed for complex, multi-step operations.

• Develop agent architectures that encompass planning, reasoning, tool utilization, memory/context, execution, reflection, validation, and error recovery.

• Integrate agents with APIs, databases, enterprise systems, developer tools, and external services.

• Create reliable tool usage and MCP-based integrations when applicable.

• Develop production-grade LLM applications using LangGraph, LangChain, or similar orchestration frameworks.

• Implement RAG, semantic search, vector retrieval, structured outputs, and other patterns for LLM applications.

• Ensure observability, evaluation, monitoring, security, and guardrails for agentic applications.

• Provide technical leadership across AI-driven software products and platforms.

• Apply software engineering principles including system design, modular architecture, API design, scalability, reliability, testing, CI/CD, and maintainability.

• Build production-quality services and APIs utilizing Python, FastAPI, Docker, Kubernetes, and cloud platforms.

• Collaborate with engineering, product, data, and client teams to translate business challenges into scalable technical solutions.

• Conduct technical design reviews and mentor AI/software engineers.

• Establish engineering standards and best practices for AI and agentic applications.

• Lead Agentic AI initiatives and influence architectural and engineering decisions across teams.

• Prototype emerging technologies and transition successful strategies into dependable production solutions.

• Work alongside clients and internal stakeholders to identify opportunities for quantifiable Agentic AI value.

⛳️ Requirements

• Over 6 years of experience in software engineering / AI engineering.

• Strong practical development experience and foundational knowledge in software engineering.

• Proven experience in building production-grade applications and services.

• Demonstrated experience in developing production-grade Agentic AI systems beyond basic chatbots or simple RAG applications.

• In-depth understanding of Agentic Evaluation / Agent Evals.

• Experience in creating evaluation datasets, test scenarios, metrics, automated regression tests, and quality gates.

• Ability to assess planning, tool utilization, reasoning trajectories, context management, reliability, safety, latency, cost, and task completion.

• Extensive hands-on experience with Python and contemporary backend/API development.

• Familiarity with LLMs, GenAI, agent orchestration, tool invocation, and RAG.

• Experience with agent frameworks such as LangGraph, LangChain, CrewAI, AutoGen, Google ADK, or similar.

• Thorough understanding of multi-agent architectures, planning, reasoning, context management, tool utilization, memory, and execution of agents.

• Experience with evaluation frameworks used to assess and enhance AI/agent performance.

• Proficient in cloud technologies, containers, CI/CD, APIs, databases, and production deployments.

• Strong grasp of software architecture, debugging, testing, scalability, and production engineering best practices.

• Practical experience using AI agents as engineering tools within the software development lifecycle.

• Experience with Claude Code / Claude Code Skills, PI, Hermes Agent, or similar agentic development platforms is highly advantageous.

• Familiarity with MCP and building MCP servers/tools is a plus.

• Experience with Claude, GPT, Gemini, Llama, or other advanced models is a plus.

• Experience with AWS, Azure, or GCP is a plus.

• Familiarity with Kubernetes, Docker, CI/CD, and cloud-native architectures is a plus.

• Understanding of LLM observability and tracing is a plus.

• Experience with Langfuse, Arize Phoenix, OpenTelemetry, or similar is a plus.

• Experience implementing automated agent evaluations, regression testing, and quality gates is a plus.

• Familiarity with distributed systems and scalable AI inference is a plus.

• Experience in consulting or client-facing environments is a plus.

🏝️ Benefits

• Comprehensive health, dental, and vision insurance.

• Flexible work hours with remote work options.

• Professional development and training opportunities.

• Collaborative and innovative work environment.

• Opportunity to work on cutting-edge AI technologies.