Sr. AI Engineer (SLM and LLM)

NexTurn; Hyderabad; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

NexTurn is seeking a senior Enterprise AI Engineer to diagnose business challenges, map data landscapes, and co-design AI solutions on-site. You will lead end-to-end design and delivery of agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications in enterprise settings.

You will architect production-grade Enterprise AI applications on Foundry Solutions or Rackspace/OpenStack GPU infrastructure, integrating with ERP/CRM systems, data warehouses, and data

Qualifications

• Diagnose critical business challenges and map data landscapes to design AI solutions on-site.
• Lead end-to-end design and delivery of agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision apps.
• Drive rapid prototyping and POCs delivering tangible business value within days to weeks.

Responsibilities

• Lead end-to-end solution design and delivery of agentic AI workflows, RAG pipelines, knowledge graphs, and real-time decision-making applications.
• Architect production-grade Enterprise AI apps on Foundry Solutions or private cloud with ERP/CRM integrations.
• Build scalable data pipelines across structured/unstructured data using ETL/ELT, vector DBs, and knowledge bases.

Skills

AI/ML delivery

LLMs & prompt engineering

Vector databases

Data pipelines

RAG pipelines

Agent orchestration

Enterprise AI

Cross-functional collaboration

Communication with execs

Education

Bachelor's degree in CS/IT/Engineering

Tools

Palantir Foundry

AIP

Uniphore BAIC

LangChain

LangGraph

CrewAI

LlamaIndex

Haystack

Pinecone

Weaviate

AstraDB

NVIDIA GPUs (H100/H200)

OpenStack

VMware

Docker

Kubernetes

Job description

• Software engineering, data engineering, or AI/ML delivery.
• Proven track record in building and deploying AI/ML applications in production at enterprise scale.
• Hands-on with LLMs, prompt engineering, vector databases, data pipelines, application dashboards, RAG pipelines, and agent orchestration frameworks.
• 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:Bachelor's degree in computer science, Information Technology, Engineering, or equivalent.

Job Description:

• 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.