GenAI Tech Lead
Confirmed on the employer's own hiring board on Oct 28, 2026. First seen by Alion on Oct 27, 2026.
Job Summary
This role is accountable for delivering advanced Generative AI solutions by leveraging expertise in Large Language Models (LLMs), prompt engineering, and modern Python frameworks. The individual applies advanced proficiency in designing, developing, and optimizing AI-driven applications, ensuring technical excellence and strategic alignment with project goals. They guide teams in implementing robust architectures and best practices, contributing to the successful execution of complex development projects.
Key Responsibilities
1. Lead solution development using GenAI, LLMs, and prompt engineering to architect and implement scalable AI applications, ensuring alignment with project requirements.
2. Develop and optimize RESTful APIs with Python frameworks such as Flask, Django, and FastAPI to enable seamless integration of AI models and data sources.
3. Design and maintain data pipelines utilizing MySQL, PostgreSQL, and VectorDB technologies (e.g., Pinecone), ensuring efficient storage and retrieval of embeddings and model outputs.
4. Implement advanced prompt engineering techniques to enhance LLM performance, tailoring prompts for specific use cases and optimizing model responses.
5. Oversee code quality and performance by conducting comprehensive code reviews and enforcing best practices in Python and AI model development.
6. Integrate Azure AI Search and other cloud-based tools to support retrieval-augmented generation and scalable deployment of GenAI solutions.
7. Collaborate within the development team to resolve technical challenges, provide guidance on architectural decisions, and ensure process compliance throughout the project lifecycle.
Skill Requirements
1. Advanced Proficiency In Genai, Llms, And Prompt Engineering For Solution Design And Implementation.
2. Solid Experience With Python And Frameworks Such As Flask, Django, And Fastapi.
3. Advanced Knowledge Of Restful Api Development And Integration.
4. Indepth Expertise In Relational And Vector Databases, Including Mysql, Postgresql, And Pinecone.
5. Advanced Skills In Embeddings, Retrievalaugmented Generation, And Cloud Ai Services (E.G., Azure Ai Search).
6. Strong Understanding Of Code Optimization, Performance Tuning, And Quality Assurance In Aicentric Projects.
Other Requirements
1. Optional but valuable:
2. Microsoft Certified: Azure AI Engineer Associate
3. - Google Professional Machine Learning Enginee