This is a permanent role with valued clients of People Impact

We are looking for a Senior / Lead Engineer to build and scale GenAI systems, including tool-calling agents and autonomous workflows. This role involves hands-on development of LLM-powered applications, agent frameworks, workflow automation, and system observability.

The ideal candidate will be comfortable working across the full lifecycle of AI systems, including design, development, testing, debugging, deployment, and documentation of agent behavior.

Key Responsibilities:

• 4–10+ years of experience in software engineering, AI/ML engineering, or AI solution delivery, including hands-on work in building and deploying intelligent applications

• Practical experience delivering GenAI, LLM-powered, or AI-enabled solutions in development, pilot, or production environments

• Strong technical foundation in Python and modern backend engineering patterns, with experience building APIs, services, and application components

• Hands-on experience with LLM platforms and AI development tools such as Azure OpenAI, Azure AI Studio, OpenAI API, AWS Bedrock, Google Vertex AI, or equivalent

• Experience working with orchestration frameworks such as Semantic Kernel, LangChain, AutoGen, or equivalent approaches for prompt workflows, tool calling, and agent coordination

• Strong working knowledge of retrieval-augmented generation (RAG), embeddings, vector search, and grounding patterns using platforms such as Azure AI Search, Pinecone, Weaviate, FAISS, or equivalent

• Experience building and deploying cloud-native AI services using tools such as Azure Functions, Azure Container Apps, FastAPI, Docker, GitHub, Azure DevOps, or equivalent engineering and deployment platforms

• Solid understanding of CI/CD, containerization, automated testing, and secure deployment practices for modern AI-enabled applications

• Familiarity with observability and operational tooling such as Application Insights, OpenTelemetry, Azure Monitor, Datadog, or New Relic, or equivalent monitoring platforms

• Experience integrating AI services with REST APIs, enterprise workflows, backend systems, or downstream business applications

• Strong problem-solving skills and ability to translate solution requirements into well-structured technical implementations

• Strong ownership mindset across the SDLC, including design, build, testing, deployment, support, and continuous improvement

• Good collaboration and communication skills, with the ability to work effectively with engineers, architects, product owners, and platform teams