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AI Tech Lead to design
Job Location:
Job Location:
Alpharetta, GA - USA
Monthly Salary:
Not provided by the employer
Monthly Salary:
Posted:
25 June 2026 (30+ days ago)
Posted:
Application Deadline:
22 September 2026
Application Deadline:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
Job Description
Role: Tech Lead (AI)
Department: Wealth Management
Location: Alpharetta GA (3 days onsite in a week)
Position Type: Fulltime
| Skill | Years of Experience |
| GenAI & MLOps |
|
| LLM RAG Elastic Search |
|
| Handson Python coding & code review |
|
| Chatbot Development |
|
| NLP |
|
| MCP |
|
Role Summary
We are seeking a hands-on AI Tech Lead to design and build enterprise-grade LLM and RAG-based solutions. The role requires strong expertise in Generative AI system design and scalable architecture along with the ability to lead development and optimize real-world AI applications.
Key Responsibilities
- Design and implement LLM-powered applications using RAG embeddings and agentic AI
- Build scalable end-to-end AI architectures integrating enterprise data
- Optimize LLM performance (RPM TPM latency cost)
- Improve accuracy by handling hallucinations and retrieval issues
- Work with Azure AI Services and AI Gateways
- Ensure data security and masking for sensitive information
- Lead hands-on development (Python /APIs)
Core Skills
- Strong experience in Generative AI LLMs and RAG
- Expertise in:
- Prompt engineering (temperature top-p)
- Vector databases & embeddings
- API integrations (OpenAI / Azure OpenAI)
- Solid coding in Python (mandatory) Java/Spring Boot (preferred)
- Experience in system design and scalable architectures
Must Have
- End-to-end LLM RAG implementation experience
- Strong problem-solving & debugging skills
- Ability to translate business requirements into technical solutions
- Prior client-facing / leadership experience
- Good to Have
- Experience with MCP Agentic AI
- Exposure to Banking / Financial domain
Ideal Candidate:
- A hands-on AI lead who can architect code hands on exp in production environment and scale real-world GenAI solutions in enterprise environments.
