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Solution Architect – AI Projects
2 weeks ago
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:
o Vector Databases (e.g., FAISS, Chroma)
o RAG Pipelines (Retrieval-Augmented Generation)
o 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:
o Vector Search Engines (e.g., FAISS, Pinecone, Chroma)
o LLM Tuning & Deployment (e.g., LLaMA, GPT, Mistral, etc.)
o RAG systems, Prompt Engineering, LangChain
o 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
