Solution Architect - Artificial Intelligence/Machine Learning

Role Overview :

We are looking for a Solution Architect with proven experience in AI/ML system design, team leadership, and successful delivery of Vector DB-based, RAG-enabled, and LLM-tuned solutions. You will act as both a technical leader and a strategic enabler, guiding developers across technologies to adopt best practices in integrating AI into products and internal processes.

This is a critical onsite role, working directly with engineering managers and developers across technologies (including .NET, Python, MERN/MEAN), ensuring scalable, maintainable, and innovative AI-driven systems.

Key Responsibilities :

Architect, plan, and deliver enterprise-grade AI solutions using :

- Vector Databases (e.g., FAISS, Chroma)

- RAG Pipelines (Retrieval-Augmented Generation)

- LLM Pre-training, Fine-tuning, and RLHF (Reinforcement Learning with Human Feedback)

- Lead AI solution design discussions and provide actionable architecture blueprints.

- Collaborate with engineering teams (Python, .NET, MERN, MEAN) to integrate AI modules into existing and new systems.

- Evaluate and select AI/ML frameworks, infrastructure, and tools suited for business needs.

- Guide and mentor junior AI engineers and full-stack developers on technical direction, code quality, and solution robustness.

- Define and implement best practices for model training, versioning, deployment, and monitoring.

- Translate business needs into technical strategies for AI adoption across products and internal processes.

- Stay ahead of emerging AI trends and continuously assess their applicability to business goals.

Required Skills & Qualifications :

- Bachelors or Masters in Computer Science, Engineering, AI/ML, or related fields.

- 5+ years of experience in software architecture with a focus on AI/ML system design and project delivery.

Hands-on expertise in :

a. Vector Search Engines (e.g., FAISS, Pinecone, Chroma)

b. LLM Tuning & Deployment (e.g., LLaMA, GPT, Mistral, etc.)

c. RAG systems, Prompt Engineering, LangChain

- RLHF techniques and supervised finetuning

- Experience working with multi-tech teams (especially .NET and JavaScript-based stacks).

- Strong command over architecture principles, scalability, microservices, and API-based integration.

- Excellent team leadership, mentorship, and stakeholder communication skills.

- Prior experience delivering at least one production-grade AI/NLP project with measurable impact.

Nice to Have :

- Experience with tools like MLflow, Weights & Biases, Docker, Kubernetes, Azure/AWS AI services

- Exposure to data pipelines, MLOps, and AI governance

- Familiarity with enterprise software lifecycle and DevSecOps practices