Sr. AI Engineer (SLM and LLM)

Sr. AI Engineer (SLM and LLM) Location: India, Remote

Work Experience: 7+ Years

• Software engineering, data engineering, or AI/ML delivery.
• Proven track record in building and deploying AI/ML applications in production at enterprise scale.
• Deep full-stack proficiency: Python (required), Node.js/Go, React/Vue, SQL/NoSQL databases.
• Hands-on with LLMs, prompt engineering, vector databases, data pipelines, application dashboards, RAG pipelines, and agent orchestration frameworks.
• DevOps skills: Docker, Kubernetes, CI/CD, GPU infrastructure, cloud-native deployment patterns.
• Ability to translate ambiguous customer needs into actionable engineering plans under tight timelines.
• Excellent communication skills - comfortable with C-suite presentations, technical workshops, and cross-functional collaboration.
• Experience with Palantir Foundry, AIP, ontology modeling, Uniphore BAIC, or similar Enterprise AI development platforms is a Plus.
• Knowledge of SLM fine-tuning, model distillation, RLHF, and AI evaluation frameworks.
• Experience building agentic AI solutions: multi-agent systems, tool use, and autonomous workflow orchestration.
• Familiarity with GPU infrastructure (NVIDIA H100/B200, InfiniBand) and private cloud platforms (OpenStack, VMware).
• Prior experience in technology consulting, AI startups, or Forward Deployed / Solutions Engineering roles.
• Domain expertise in financial services, healthcare, supply chain, defense, energy, or manufacturing.
• Experience with knowledge graphs, semantic modeling, and ontology-driven data management.
• Experience integrating across heterogeneous enterprise systems - ERP, data warehouses, data lakes, streaming architectures.

Qualifications: Bachelors degree in computer science, Information Technology, Engineering, or equivalent.

• Diagnose critical business challenges, map data landscapes, and co-design AI solutions on-site.
• Lead end-to-end solution design and delivery of agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications.
• Drive rapid prototyping and POCs that demonstrate tangible business value within days to weeks.
• Serve as the primary technical owner across the full project lifecycle: scoping, architecture, build, deployment, and post-launch optimization.
• Architect production-grade Enterprise AI applications on Partner Foundry Solutions or Rackspace Private Cloud and GPU infrastructure, integrating with enterprise systems (ERP, CRM, data warehouses, data lakes).
• Build scalable data pipelines across structured and unstructured data using ETL/ELT, vector databases (Pinecone, Weaviate, AstraDB), and knowledge base frameworks.
• Develop and fine-tune LLM/SLM solutions; implement RAG architectures (LlamaIndex, Haystack) and orchestrate multi-agent workflows (LangChain, LangGraph, CrewAI).
• Ship with full-stack and DevOps depth: Python, Node.js/Go, React/Vue, Docker, Kubernetes, CI/CD, and GPU cluster management.
• Champion observability, monitoring, and telemetry to ensure trustworthy, auditable, and versioned AI agents in production.
• Identify expansion opportunities by working with sales and customer success to uncover high-value use cases across new business domains.
• Feed structured field insights back to Platform Engineering and Product on feature gaps, emerging needs, and usability improvements.
• Build reusable IP through reference architectures, accelerators, frameworks, and technical best practices that scale future engagements.
• Mentor engineers and customer teams, driving knowledge transfer and building internal AI competencies.