Principal Gen AI Scientist — Lead AI Agents & GenAI Apps

Compunnel Inc.; McLean (VA); On-site; USD 190,000 - 260,000; Full time

Job summary

A technology solutions company is looking for a Principal Gen AI Scientist with expertise in Generative AI to lead the design and development of AI Agents and applications. The role requires a minimum of 10 years in AI/ML, focusing on LLM-based solutions. Candidates should have a strong programming background, particularly in Python, as well as experience with AWS services. This position involves working in a collaborative agile environment, integrating innovative GenAI solutions for complex business challenges.

Qualifications

• 10+ years of experience in AI/ML, specifically in GenAI or LLM-based solutions.
• Expertise in prompt engineering, fine-tuning, RAG, GraphRAG, and vector databases.
• Ability to work in cross-functional agile teams.

Responsibilities

• Architect and implement scalable AI Agents and GenAI applications.
• Develop and fine-tune lightweight LLMs and evaluate models such as Claude and Azure OpenAI.
• Integrate GenAI solutions with enterprise platforms via APIs.

Skills

Advanced proficiency in LLMs

Expertise in prompt engineering

Strong programming skills in Python

Experience with AWS services

Ability to work in cross-functional teams

Education

MS/PhD in AI/Data Science

Tools

AWS SageMaker

MLFlow

Kubernetes (EKS)

Job description

We are looking for a Principal Gen AI Scientist with deep expertise in Generative AI to lead the design and development of AI Agents, Agentic Workflows, and Gen AI applications for complex business challenges.

This role requires advanced proficiency in LLMs, RAG architectures, multi-modal AI, and AWS-based deployments.

Key Responsibilities

• Architect and implement scalable AI Agents, Agentic Workflows, and GenAI applications.
• Develop and fine-tune lightweight LLMs; evaluate models such as Claude (Anthropic), Azure OpenAI, and open-source alternatives.
• Design and deploy Retrieval-Augmented Generation (RAG) and Graph RAG systems using vector databases and knowledge bases.
• Curate enterprise data and integrate with AWS Bedrock Knowledge Base/Elastic.
• Implement solutions leveraging MCP (Model Context Protocol) and A2A (Agent-to-Agent) communication.
• Build and maintain Jupyter-based notebooks using SageMaker and MLFlow/Kubeflow on Kubernetes (EKS).
• Collaborate with cross-functional teams to deliver full-stack Gen AI experiences.
• Integrate GenAI solutions with enterprise platforms via APIs and standardized patterns.
• Establish validation procedures with Evaluation Frameworks, bias mitigation, and safety protocols.
• Design and build robust ingestion pipelines for unstructured data (PDFs, video, audio) using semantic chunking and privacy controls.
• Orchestrate multimodal pipelines using scalable frameworks (Apache Spark, PySpark).
• Implement embeddings and integrate with vector stores for RAG architectures.

Required Qualifications

• MS/PhD in AI/Data Science.
• 10+ years of experience in AI/ML, with 3+ years in applied GenAI or LLM-based solutions.
• Expertise in prompt engineering, fine-tuning, RAG, GraphRAG, and vector databases.
• Proven experience with AWS SageMaker, Bedrock, MLFlow on EKS.
• Strong programming skills in Python and ML libraries (Transformers, LangChain).
• Deep understanding of Gen AI system patterns, architectural best practices, and evaluation frameworks.
• Ability to work in cross-functional agile teams.
• Github Code Repository link required for each candidate.

Preferred Qualifications

• Published contributions or patents in AI/ML/LLM domains.
• Hands-on experience with enterprise AI governance and ethical deployment frameworks.
• Familiarity with CI/CD practices for ML Ops and scalable inference APIs.
• Experience building AI agents and deploying Gen AI applications to production.