The ideal candidate will be responsible for leading a team of software engineers to design, develop, test, and maintain software applications. The Lead Software Engineer will collaborate with other departments to ensure that software applications meet business requirements and user needs while providing technical guidance and leadership to the team.
- Lead the software development team:
o Lead a team of software engineers in designing, developing, testing, and maintaining software applications.
o Set and communicate clear expectations for the team regarding project timelines, quality standards, and deliverables.
o Provide technical guidance and mentorship to team members.
o Conduct regular performance reviews and provide feedback to team members.
- Design and develop software Modules:
o Design and develop software modules using design principles and tools.
o Ensure that software applications meet functional requirements and are reliable.
o Develop and execute software test plans.
- Troubleshoot and debug complex software issues:
o Identify and fix complex bugs in software applications.
o Provide technical support to end-users.
- Collaborate with cross-functional teams:
o Work with other teams such as product management, quality assurance, and user experience to ensure that software applications meet business requirements and user needs.
o Communicate effectively with team members and stakeholders.
- Owning code quality delivered by the team:
o Review code written by team members, offer feedback, and contribute to the codebase as needed.
o Ensure that code meets coding standards and best practices.
- Stay up to date with emerging trends and technologies:
o Keep up to date with emerging trends and technologies in the software development industry.
o Make recommendations for improvements to existing software applications and processes.
- Owning Design Documentation:
o Documenting software design, patterns, and key decisions ensuring that they are clear and concise and can be easily understood by other team members.
o Ensuring that documentation is up to date.
- Identify and implement coding standards and best practices:
o Identify coding standards and best practices, ensuring that software applications are developed in a consistent and high-quality manner.
o Own the implementation of coding standards and best practices.
- Responsible for Configuration Management and Release plan Documentation.
- 2+ years delivering enterprise-grade GenAI systems in production, including RAG pipelines, multi-agent and agentic workflows, function/tool calling, and MCP-based integrations with enterprise systems. Experience must extend beyond proofs of concept into live, business-critical deployments.
- 3+ years on a major cloud (AWS / Azure / GCP) and modern DevOps pipelines, including containers, infrastructure-as-code, and CI/CD, with hands-on ownership of deployment, observability, and cost and latency tuning for AI workloads.
- End-to-end delivery ownership, with a track record of working alongside architects and project managers to take AI initiatives from discovery through production rollout and steady-state operations.
- Strong grasp of GenAI evaluation, observability, and safety, with experience building evaluation harnesses, monitoring for hallucinations, tracking cost and latency, and implementing guardrails against prompt injection.
- Strong cross-functional collaboration, having worked alongside security, data engineering, and QA teams, and engaged directly with client SMEs through the delivery lifecycle.
- Team leadership of 3+ AI engineers, including mentoring, code reviews, and the ability to translate between business stakeholders and the engineering team.
Must-have: Python, LLM APIs (OpenAI, Azure OpenAI, Anthropic, or Gemini), RAG architecture (chunking, embeddings, re-ranking), vector databases (Pinecone, Weaviate, pgvector, or Azure AI Search), agentic frameworks (LangChain, LangGraph, CrewAI, or AutoGen), MCP and function/tool calling, prompt engineering, LLM evaluation tooling (Ragas, LangSmith, or custom harnesses), at least one major cloud (AWS, Azure, or GCP), Docker, Kubernetes, CI/CD, infrastructure-as-code (Terraform), FastAPI and microservices.
Good to have: Fine-tuning (LoRA or QLoRA), open-source LLMs (Llama, Mistral, or Qwen), voice and vision agents, GraphRAG and knowledge graphs (Neo4j).
- Bachelor’s degree in computer science or related field.
- 6-9 years of experience in software development.
- Proven leadership experience in leading software development teams.
- Knowledge of software development methodologies such as Agile or Scrum.
- Ability to mentor and train junior team members.
