llm optimization & adaptation senior engineer for newra, part of accenture r00337923

At Accenture Newra AI Hub, we are not just building technology, we are redefining how banking operates. As part of our strategic collaboration with Piraeus, Newra is designed to responsibly embed AI at the core of its business, moving beyond experimentation to real-world impact at scale. Built to make a real difference, Newra reflects our belief that AI creates value only when it genuinely improves people’s lives.

You will work on advanced AI solutions that span the full spectrum of the bank -from core banking systems to customer experience- simplifying complexity, automating critical processes and delivering measurable results where they matter most.

Joining Newra means becoming part of a high-performing team of innovators at the beginning of a major reinvention. This is a space for people who approach AI with depth, discipline and purpose. You will collaborate across disciplines, develop future-proof skills, and help turn technology into real-world transformation.

What you 'll build

You'll help shape how the bank evaluates, adapts, and optimizes LLM and SLM capabilities for enterprise use cases. You'll work on model selection, benchmarking, fine-tuning patterns, prompt and retrieval optimization, and cost-performance improvements across AI solutions, building the evaluation rigor and optimization patterns that improve reliability, safety, latency, and measurable business impact.

Responsibilities:

• Model evaluation and benchmarking frameworks for LLM, SLM, and agentic AI use cases

• Model selection recommendations based on accuracy, latency, cost, safety, explainability, and operational constraints

• Fine-tuning, LoRA / PEFT, prompt optimization, and retrieval optimization experiments for priority business use cases

• Distillation and model compression proof points where smaller or more efficient models can deliver sufficient performance

• Evaluation datasets, test harnesses, golden-answer sets, and regression testing routines for AI applications

• Observability dashboards and quality feedback loops covering model performance, hallucination risk, drift, cost, and user feedback

• Target-state patterns for open-weight or self-hosted LLM adoption, including architecture, governance, and operational readiness consideration

Qualification

What we need

• B.Sc. M.Sc. or equivalent experience in CS, Engineering, AI, Data Science, Machine Learning, or related field

• Strong Python skills, hands-on experience in ML/LLM engineering & production-grade AI experimentation

• Good understanding of LLMs, SLMs, open-weight models, model families, context windows, token economics, latency, accuracy, and cost trade-offs

• Experience with model evaluation, benchmarking, test sets, quality metrics, regression testing, and human evaluation workflows

• Hands-on exposure to fine-tuning, LoRA / PEFT, prompt optimization, retrieval optimization, or model adaptation techniques

• Familiarity with RAG, GraphRAG, embeddings, vector search, retrieval quality improvement

• Experience with MLflow, W&B, LangSmith, Langfuse, or similar experiment tracking and observability tools

• Comfortable working with engineering teams to translate model insights into production-ready AI patterns

Nice to have:

• Experience with Hugging Face, PyTorch, transformers, quantization, model compression, or distillation

• Awareness of self-hosted / open-weight LLM architecture, deployment, monitoring, and governance considerations

• Experience with Azure AI Foundry, Azure ML, Databricks, or enterprise AI platforms

• Understanding of regulated environments, model risk, Responsible AI, data privacy, and banking compliance requirements

What's in it for you

• Competitive salary and benefits, including but not limited to: life/health insurance, performance based bonuses, monthly vouchers, company car (depending on management level), flexible work arrangements, employee share purchase plan, parental leave and various corporate discounts

• Continuous training & development through global platforms & local academy. At Accenture, we believe in bringing the best to our clients through continuous learning & improvement – from basic skills to industry-specific content – available to all our people

• Career coaching and mentorship to help you manage your career and develop professionally

• Ongoing strength and skill-based evaluation process

• Various opportunities to develop your career across a spectrum of clients, industries and projects

• Diverse and inclusive culture

• Opportunities to get involved in corporate citizenship initiatives, from volunteering to doing charity work

• Under our Brain Regain initiative, extra relocation benefits may apply