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Lead AI Engineer
Luxoft
Abu Dhabi, UAE
Full-time
Lead · 8+ years experience
Onsite
Discovered 6 days ago
• Minimum of 8 years' experience in enterprise-grade developer roles. • Minimum of 3 years' relevant experience in AI-specific applications in an enterprise context, including some experience guiding, reviewing or coordinating the work of other engineers. • Bachelor's or master's degree in computer science or related discipline, or equivalent combined education and experience. • Technical experience in financial domain AI: Track record in building and leading the delivery of generative AI applications for financial services (trading, compliance, customer support). Experience in fixed income — bonds, FX, credit — would be preferred. • AI and LLM Integration: Python expertise, leveraging large language models (GPT-4, Claude) within AI pipelines. Experience with LangChain and LangGraph for orchestrating generative workflows and agentic • Generative AI Pipelines: Ability to design and own multi-step, retrieval-augmented generation (RAG) pipelines using Azure Cognitive Search to integrate structured/unstructured company data effectively, and to set the patterns the wider team re-uses behaviours, and for guiding other engineers' use of these frameworks. • Agentic System Design: Experience developing autonomous AI agents that handle context-aware interactions, leveraging recent advancements from OpenAI's Agents SDK. • Fine-Tuning and Customization (Optional): Practical experience fine-tuning or adapting LLMs to specific business tasks using modern techniques (LoRA, PEFT). • DevOps and Deployment: Familiar with CI/CD practices, containerization (Docker), orchestration (Kubernetes), and observability tools for deployment in regulated environments. • Excellent interpersonal skills, including collaboration, facilitation, and negotiation. • Excellent planning and organizational skills, including the ability to plan and sequence a workstream's deliverables and coordinate the effort of other engineers contributing to it.
Key Skills for This Role
• Minimum of 8 years' experience in enterprise-grade developer roles. • Minimum of 3 years' relevant experience in AI-specific applications in an enterprise context, including some experience guiding, reviewing or coordinating the work of other engineers. • Bachelor's or master's degree in computer science or related discipline, or equivalent combined education and experience. • Technical experience in financial domain AI: Track record in building and leading the delivery of generative AI applications for financial services (trading, compliance, customer support). Experience in fixed income — bonds, FX, credit — would be preferred. • AI and LLM Integration: Python expertise, leveraging large language models (GPT-4, Claude) within AI pipelines. Experience with LangChain and LangGraph for orchestrating generative workflows and agentic • Generative AI Pipelines: Ability to design and own multi-step, retrieval-augmented generation (RAG) pipelines using Azure Cognitive Search to integrate structured/unstructured company data effectively, and to set the patterns the wider team re-uses behaviours, and for guiding other engineers' use of these frameworks. • Agentic System Design: Experience developing autonomous AI agents that handle context-aware interactions, leveraging recent advancements from OpenAI's Agents SDK. • Fine-Tuning and Customization (Optional): Practical experience fine-tuning or adapting LLMs to specific business tasks using modern techniques (LoRA, PEFT). • DevOps and Deployment: Familiar with CI/CD practices, containerization (Docker), orchestration (Kubernetes), and observability tools for deployment in regulated environments. • Excellent interpersonal skills, including collaboration, facilitation, and negotiation. • Excellent planning and organizational skills, including the ability to plan and sequence a workstream's deliverables and coordinate the effort of other engineers contributing to it.
Full Job Posting
Responsibilities
- Development of existing and new modules within core applications supporting the front office investment teams • Delivering new functionality, data capabilities and modules as well as smaller enhancements and fixes to existing modules • Engagement with IT and business stakeholders and take ownership of deliverables. • Understand business problems and offer technical solutions. • Contribute to continuous improvement with respect to coding standards, practices and SDLC maturity. • Work in partnership with quants and traders to help building, supporting and maintaining a quantitative trading and risk optimization platform. • Engage with stakeholders and take ownership of deliverables. • Improve productivity by using automation (where applicable).
- Development of existing and new modules within core applications supporting the front office investment teams
- Delivering new functionality, data capabilities and modules as well as smaller enhancements and fixes to existing modules
- Engagement with IT and business stakeholders and take ownership of deliverables.
- Understand business problems and offer technical solutions.
- Contribute to continuous improvement with respect to coding standards, practices and SDLC maturity.
- Work in partnership with quants and traders to help building, supporting and maintaining a quantitative trading and risk optimization platform.
- Engage with stakeholders and take ownership of deliverables.
- Improve productivity by using automation (where applicable).
Skills
- Minimum of 8 years' experience in enterprise-grade developer roles. • Minimum of 3 years' relevant experience in AI-specific applications in an enterprise context, including some experience guiding, reviewing or coordinating the work of other engineers. • Bachelor's or master's degree in computer science or related discipline, or equivalent combined education and experience. • Technical experience in financial domain AI: Track record in building and leading the delivery of generative AI applications for financial services (trading, compliance, customer support). Experience in fixed income — bonds, FX, credit — would be preferred. • AI and LLM Integration: Python expertise, leveraging large language models (GPT-4, Claude) within AI pipelines. Experience with LangChain and LangGraph for orchestrating generative workflows and agentic • Generative AI Pipelines: Ability to design and own multi-step, retrieval-augmented generation (RAG) pipelines using Azure Cognitive Search to integrate structured/unstructured company data effectively, and to set the patterns the wider team re-uses behaviours, and for guiding other engineers' use of these frameworks. • Agentic System Design: Experience developing autonomous AI agents that handle context-aware interactions, leveraging recent advancements from OpenAI's Agents SDK. • Fine-Tuning and Customization (Optional): Practical experience fine-tuning or adapting LLMs to specific business tasks using modern techniques (LoRA, PEFT). • DevOps and Deployment: Familiar with CI/CD practices, containerization (Docker), orchestration (Kubernetes), and observability tools for deployment in regulated environments. • Excellent interpersonal skills, including collaboration, facilitation, and negotiation. • Excellent planning and organizational skills, including the ability to plan and sequence a workstream's deliverables and coordinate the effort of other engineers contributing to it.
Qualifications
- Must have
- Minimum of 8 years' experience in enterprise-grade developer roles.
- Minimum of 3 years' relevant experience in AI-specific applications in an enterprise context, including some experience guiding, reviewing or coordinating the work of other engineers.
- Bachelor's or master's degree in computer science or related discipline, or equivalent combined education and experience.
- AI and LLM Integration: Python expertise, leveraging large language models (GPT-4, Claude) within AI pipelines. Experience with LangChain and LangGraph for orchestrating generative workflows and agentic
- Generative AI Pipelines: Ability to design and own multi-step, retrieval-augmented generation (RAG) pipelines using Azure Cognitive Search to integrate structured/unstructured company data effectively, and to set the patterns the wider team re-uses behaviours, and for guiding other engineers' use of these frameworks.
- Agentic System Design: Experience developing autonomous AI agents that handle context-aware interactions, leveraging recent advancements from OpenAI's Agents SDK.
- DevOps and Deployment: Familiar with CI/CD practices, containerization (Docker), orchestration (Kubernetes), and observability tools for deployment in regulated environments.
- Excellent interpersonal skills, including collaboration, facilitation, and negotiation.
- Excellent planning and organizational skills, including the ability to plan and sequence a workstream's deliverables and coordinate the effort of other engineers contributing to it.
Preferred Qualifications
- Technical experience in financial domain AI: Track record in building and leading the delivery of generative AI applications for financial services (trading, compliance, customer support). Experience in fixed income — bonds, FX, credit — would be preferred.
- Fine-Tuning and Customization (Optional): Practical experience fine-tuning or adapting LLMs to specific business tasks using modern techniques (LoRA, PEFT).
- Knowledge of the finance industry
About Luxoft
Technology10,001+Founded 2000
Global IT services and consulting company
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