At Prolifics, we are currently implementing multiple solutions and we are looking to hire talented Sr AI LLM lead for our development centre in India. This position would be based out of Hyderabad and is a permanent position.

If you are looking for a high growth company with rock-solid stability, if you thrive in the energetic atmosphere of high-profile projects, we want to talk to you today! Let’s connect and explore possibilities of having you onboard the Prolifics team!

Job Title: Sr AI LLM lead           

Primary Skill: Transformer architectures, LLM fine-tuning, and instruction

Secondary Skill: RAG systems, embedding models, and retrieval

Location: Hyderabad                                        

Educational Qualification: B.Tech/BE/M.Tech/MCA/M.Sc

YOE: 6-8 yrs

Job Description:

Overview

The Principal LLM Engineer will lead the design, fine-tuning, and optimization of large language model (LLM) systems that capture, contextualize, and deliver organizational expertise at scale. This role focuses on turning unstructured and tacit knowledge into intelligent, context-aware reasoning systems that support diagnostics, decision-making, and automation across the enterprise.

Key Responsibilities

LLM Architecture s Optimization

• Design and implement LLM-based reasoning frameworks for domain-specific knowledge activation and expert
• Architect Retrieval-Augmented Generation (RAG) pipelines integrating structured, semi-structured, and unstructured enterprise knowledge
• Fine-tune and optimize foundation models for specific enterprise use cases (diagnostics, troubleshooting, process guidance, ).
• Develop prompt orchestration frameworks, including hierarchical prompts, context injection, and adaptive prompt
• Evaluate new LLM modalities (multimodal, reasoning-augmented, tool-using models) for continuous system

Knowledge Engineering s Representation

• Collaborate with knowledge engineers to structure and embed expert content from documents, logs, and SME interviews.
• Develop semantic embedding strategies, vector stores, and hybrid retrieval methods combining symbolic and statistical
• Create and maintain domain ontologies and entity graphs to ground model outputs in factual, validated enterprise
• Ensure model interpretability through citation, provenance tracking, and source- grounded

Agentic s Multi-Model Integration

• Integrate LLMs within multi-agent architectures, enabling autonomous reasoning and tool-assisted execution.
• Work with Agentic AI architects to design LLM–tool interaction schemas and context handoff mechanisms.
• Build adaptive memory systems combining vector, relational, and graph storage
• to support contextual continuity and learning loops.

Performance, Safety s Evaluation

• Establish evaluation pipelines for accuracy, coherence, grounding, and bias mitigation.
• Implement reinforcement learning from human feedback (RLHF) or in-context learning feedback loops.
• Design A/B testing frameworks for comparing model prompts, architectures, and retrieval
• Partner with governance and security teams to ensure compliance with data privacy and ethical AI standards.

Required Skills s Expertise

Core (LLM Engineering s Optimization)

• Deep expertise with transformer architectures, LLM fine-tuning, and instruction
• Strong experience with RAG systems, embedding models, and retrieval
• Familiarity with multi-agent orchestration frameworks (AutoGen, Semantic Kernel, LangChain Agents).
• Proficiency in Python, PyTorch, and distributed inference optimization.
• Understanding of prompt engineering, context window management, and token efficiency

Knowledge Systems s Data Foundations

• Experience building and maintaining knowledge graphs, vector databases, andcontext retrieval APIs.
• Ability to structure domain-specific taxonomies and embeddings for technical and industrial use cases.
• Familiarity with knowledge provenance, explainability, and citation generation mechanisms.

Evaluation s Experimentation

• Expertise in designing model evaluation metrics, including factual accuracy, reasoning depth, and human preference modeling.
• Strong analytical background for evaluating LLM performance across complex domain- specific tasks.

Preferred Qualifications

• 7+ years of experience in applied NLP, ML, or AI systems
• 2+ years hands-on with LLM fine-tuning, retrieval-augmented systems, or enterprise AI
• Graduate degree in Computer Science, Machine Learning, Computational Linguistics, or related
• Background in industrial, engineering, or diagnostics-related domains

About us:

Prolifics Corporation Limited is a Global Technology Solutions Provider with presence across North America (USA and Canada), Europe (UK and Germany), Middle East & Asia. In India, we have off shore development centers: 3 in Hyderabad & 1 in Pune.

For more than 40 years, Prolifics has transformed enterprises of all sizes including over 100 Fortune 1000 companies by solving their complex IT challenges. Our clients include Fortune 50 and Fortune 100 companies across a broad range of industries including Financial Services, Insurance, Government, Healthcare, Telecommunications, Manufacturing and Retail. We rank consistently in Dream Companies to Work For and Dream Employer of the Year ranking from World HRD Congress, ranked 7 in 2019.

We encourage you to visit us on www.prolifics.com or follow us on Twitter, LinkedIn, Facebook, YouTube and other social media to know more about us.