LLM Optimization & Adaptation Senior Engineer for Newra, Part of Accenture
Quick Summary
Model evaluation and benchmarking frameworks for LLM, SLM, and agentic AI use cases Model selection recommendations based on accuracy, latency, cost, safety, explainability,
ARE YOU READY to step into the New Era (NewRA) of AI-driven banking?
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.
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
~1 min read- →
Model evaluation and benchmarking frameworks for LLM, SLM, and agentic AI use cases
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Model selection recommendations based on accuracy, latency, cost, safety, explainability, and operational constraints
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Fine-tuning, LoRA / PEFT, prompt optimization, and retrieval optimization experiments for priority business use cases
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Distillation and model compression proof points where smaller or more efficient models can deliver sufficient performance
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Evaluation datasets, test harnesses, golden-answer sets, and regression testing routines for AI applications
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Observability dashboards and quality feedback loops covering model performance, hallucination risk, drift, cost, and user feedback
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Target-state patterns for open-weight or self-hosted LLM adoption, including architecture, governance, and operational readiness consideration
Requirements
~2 min readB.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
To learn more about Accenture, and how you will be challenged and inspired from Day 1, please visit our website accenture.com/gr-en/.
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Visit us at www.accenture.com
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, sexual orientation, gender identity or expression, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
Location & Eligibility
Listing Details
- First seen
- September 29, 2026
- Last seen
- September 29, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 55%
- Scored at
- September 30, 2026
Signal breakdown
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