Artificial Intelligence Lead/Architect

Key Responsibilities :

- Design and architect end-to-end, enterprise-grade AI/ML systems with a focus on scalability, compliance, and security.

- Lead and participate in highly agile, iterative development cycles using Azure DevOps sprints, ensuring rapid delivery and continuous improvement.

- Architect and oversee solutions utilizing CrewAI and Langraph frameworks for advanced AI orchestration (mandatory).

- Guide teams using Python and C# for AI solution development and integration.

- Define Retrieval Augmented Generation (RAG) pipelines, including vector database

integration, knowledge ingestion, and caching layers.

- Architect dynamic system prompts, context memory, and persona alignment frameworks.

- Implement model routing strategies to optimize performance, accuracy, and cost.

- Establish best practices for CI/CD pipelines, MLOps, and cloud-native AI deployments.

- Ensure infrastructure meets compliance standards.

- Oversee the SDLC for AI initiatives, ensuring best practices in requirements gathering, design,

implementation, testing, deployment, and ongoing support.

- Drive rapid prototyping and MVP delivery, balancing speed with quality and scalability.

- Foster a culture of innovation, encouraging experimentation and continuous learning within

the team.

- Collaborate closely with data engineers, AI engineers, and product stakeholders to align system design with business objectives.

- Provide technical leadership, mentoring, and architectural oversight for engineering teams.

Required Qualifications :

- 10+ years of experience in AI/ML architecture and enterprise solution design.

lifecycle (SDLC), including requirements analysis, system design, development, testing,

deployment, and maintenance.

- Proven ability to deliver enterprise-grade AI solutions from concept to production, ensuring

alignment with business goals and technical standards.

- Hands-on experience managing and delivering projects using Azure DevOps sprints or similar

agile tools.

- Proficiency in both Python and C# programming languages.

- Deep expertise with CrewAI and Langraph (mandatory).

- Strong expertise in LLM fine-tuning, LoRA/QLoRA, quantization, and system prompt

engineering.

- Deep knowledge of RAG pipelines, vector databases, and semantic search.

- Proficiency with cloud platforms (GCP Vertex AI preferred; AWS SageMaker or Azure ML

acceptable).

- Proven track record in architecting scalable, distributed AI systems.

- Excellent communication, stakeholder management, and technical documentation skills.

- Strong research skills and a proactive, self-driven approach to problem-solving and

technology evaluation.

- Willingness and ability to overlap with USA Eastern Time for at least 34 hours daily to

collaborate with distributed teams.

Nice-to-Have Skills :

- Experience with Microsoft Semantic Kernel.

- Prior work in regulated industries (healthcare, finance, insurance).

- Strong understanding of compliance, data security, and risk frameworks.