Digital & GenAI Analyst - Consulting at HEXAWARE

, , India -

Full Time

Start Date

Immediate

Expiry Date

18 Oct, 26

Salary

0.0

Posted On

20 Jul, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

LLM Finetuning, Reinforcement Learning, Agentic Systems, Model Evaluation, SFT, DPO, RLHF, RLAIF, System Design, AI Strategy, Multi-agent Workflows, Synthetic Evaluation, Token Economics, Production Systems, Reliability Standards, First Principles Thinking

Industry

IT Services and IT Consulting

Description

Role Summary Build the “truth and control layer” for enterprise AI �� Why this role exists Most teams are busy building AI. We are focused on something harder: How do you evaluate, control, and trust non-deterministic AI systems at scale? At Hexaware’s AI Center of Excellence, we are building a research-driven applied AI unit, st-ABEL (Structural Theory for Agentic Behavior and Evaluation Lab); focused on: · Model evaluation and finetuning · Agentic systems and behavioral control · Evaluation-as-a-Service platforms We are looking for leaders who can think from first principles and shape AI thinking —not just use what exists. �� What you’ll work on · Design LLM finetuning and RL pipelines (SFT, DPO, RLHF/RLAIF) · Build evaluation frameworks for models, agents, and AI systems · Architect agentic systems (multi-agent workflows, tool use, planning) · Create simulation environments and synthetic evaluation setups · Define benchmarks and reliability standards for enterprise AI · Translate research ideas into production systems · Shape AI strategy (cost, performance, token economics, infra trade-offs) �� We are hiring for 2 complementary profiles: · Model Intelligence Lead → finetuning, RL, evaluation science · Agentic Systems Lead → agents, behavior, system design The Principal AI Research Consultant is responsible for designing next-generation AI systems with a focus on model evaluation, finetuning, agentic behavior, and system-level reliability. The role anchors the organization across model truth and system control and is expected to translate research concepts into production-grade systems, tools, and reusable platforms. This role requires a combination of deep technical expertise, systems thinking, and the ability to convert ideas into scalable tools and frameworks. · Aligned with st-ABEL’s identity as a research + applied systems lab Key Responsibilities

Responsibilities

Design and build the truth and control layer for enterprise AI, focusing on model evaluation, finetuning, and agentic behavior. Translate research concepts into production-grade systems and reusable platforms within the st-ABEL lab.