Senior AI Engineer – LLM Fine-Tuning / Model Engineering

Tech Mahindra; Abu Dhabi; Presencial; AED 150.000 - 210.000; Jornada completa

Descripción de la vacante

Tech Mahindra seeks a senior AI/GenAI engineer in the UAE to design, fine-tune, and deploy open-weight models for financial services. You will work across trading, research, compliance and productivity use cases, delivering production-grade AI solutions with robust evaluation and benchmarking.

The role emphasizes model adaptation, LangChain workflows, and Azure OpenAI platforms, collaborating with quants and business stakeholders in an agile environment.

Formación

• 5+ years of enterprise software development and hands-on AI/GenAI experience.
• Strong Python development and production AI/LLM engineering experience.
• Proven experience building Generative AI solutions for financial services (trading, ops, research, compliance or productivity).
• Hands-on LLM fine-tuning and model adaptation (LoRA/QLoRA, PEFT, supervised fine-tuning, preference tuning).

Responsabilidades

• Fine-tune and deploy open-weight models into production with containerized inference.
• Build and evaluate AI/ML pipelines using LangChain, LangGraph or Semantic Kernel for GenAI workflows.
• Collaborate with quants, traders and stakeholders to translate business needs into AI solutions.

Conocimientos

Python development

GenAI / LLM engineering

Open-weight models

LangChain / semantic tools

Azure OpenAI / Azure ML

Model fine-tuning / PEFT

Docker / Kubernetes / CI/CD

Production AI deployment

Model evaluation & benchmarking

Stakeholder communication

Educación

Bachelor/Master in Computer Science

Herramientas

Azure OpenAI

Azure ML

Azure Cognitive Search

Docker

Kubernetes

CI/CD tooling

Descripción del empleo

• 5+ years of enterprise software development, including 2+ years of hands-on AI/GenAI experience
• Strong Python development and production AI/LLM engineering experience
• Proven experience building Generative AI solutions for financial services, including trading, investment operations, research, compliance or productivity use cases
• Deep hands-on LLM fine-tuning and model adaptation experience:
• LoRA / QLoRA
• PEFT
• Supervised fine-tuning
• Preference tuning
• Experience deploying fine-tuned/custom models into production, including containerized inference, GPU infrastructure, model registries and model-serving frameworks
• Strong model evaluation and benchmarking skills — comparing base, fine-tuned, distilled and RAG approaches using quality, latency, throughput and cost metrics
• Practical experience with open-weight models, such as Llama, Mistral/Mixtral, Qwen, Gemma, Phi or similar
• Experience with LangChain, LangGraph and/or Semantic Kernel for GenAI workflows and agentic applications
• Strong Microsoft Azure experience, particularly Azure OpenAI, Azure Machine Learning and Azure Cognitive Search; AWS exposure is a plus
• Strong RAG, semantic retrieval and conversational memory experience
• Experience with Docker, Kubernetes, CI/CD and observability for enterprise AI deployment
• Ability to work with quants, traders and business stakeholders and translate business requirements into AI/model solutions
• Strong problem-solving, communication, stakeholder management and Agile delivery skills
• Bachelor's/Master's degree in Computer Science or equivalent experience

This role has a much stronger model-engineering focus, particularly around fine-tuning, open-source models, evaluation/benchmarking and production deployment of customized models.