Lead GenAI Engineer (Specialist - Data Sciences)

LTM

$135K — $160K *
Information Technology
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or related quantitative field
  • 10 years of experience in Enterprise Application development, specifically delivering AI/ML solutions in production
  • Deep expertise in Python and cloud-native AI stacks (Azure AI, AWS Bedrock, GCP Vertex AI)
  • Experience with frameworks like Lang Graph and Lang Chain
  • Strong foundation in microservices, API design, and enterprise security protocols

Responsibilities

  • Lead the development of production-ready AI systems using expert-level proficiency in Python or PySpark
  • Apply advanced algorithms and software design patterns to develop solutions for financial services
  • Architect high-scale solutions with a focus on performance and infrastructure cost optimization
  • Manage the transition from MVP to fully deployed AI solutions with change control processes
  • Design and deploy sophisticated RAG pipelines and Transformer-based architectures for generative AI
  • Build autonomous agents to automate complex business workflows
  • Take ownership of model lifecycle, ensuring compliance with Model Risk Management standards
  • Drive User Acceptance Testing aimed at achieving specific business outcomes

Benefits

  • Collaboration with cutting-edge AI research and development
  • Opportunity to mentor and lead a high-performing technical team
  • Engagement with C-suite stakeholders and various client ecosystems
  • Involvement in the AI Center of Excellence for innovative solution deployment
  • Potential for participation in global AI solution delivery and assurance
Full Job Description
Role description

Title: Lead GenAI Engineer

Location: Irving, Tx

1. Engineering Production Grade Development
• Handson Coding Lead the development of production ready systems with expert level proficiency in Python or PySpark
• Solution Engineering Apply advanced data structures algorithms and software design patterns to solve real world financial services challenges
• Scalability Performance Architect high scale solutions with a big picture approach ensuring system latency and infrastructure costs are optimized to drive tangible business value
• Lifecycle Management Own the transition from MVP to live solutions managing change control and enterprise level AI integration

2. Advanced AI Implementation RD 40
• Generative AI RAG Design and deploy sophisticated RAG pipelines and Transformer based architecture Orchestrate LLMasaService eg GPT4 Gemini Vertex AI alongside local SLMs eg Llama 3 Mixtral
• Agentic Workflows Build autonomous agents using frameworks such as Lang Graph preferred Crew AI or Auto Gen to automate complex multistep business logic
• MLOps Governance Take full ownership of the model lifecycle including finetuning LLMSLM monitoring model drift ground truth validation and ensuring compliance with Model Risk Management MRM standards
• UAT Validation Drive User Acceptance Testing UAT focused on specific business outcomes and accuracy benchmarks

3. Leadership Solution Orchestration
• Stakeholder Management Navigate complex client ecosystems acting as the primary technical liaison for both Csuite stakeholders and engineering teams
• Strategic Communication Translate high level business requirements into sustainable high value generative AI solutions
• CoE Liaison Partner with the BFS AI CoE to bring cutting-edge RD and incubated solutions and active participation for multiple client AI solutions demo and delivery assurance to global clients
• Team Mentorship Lead and inspire a high performing technical team fostering a positive solution mind and an initiative taking culture

Technical Qualifications
• Education bachelors or masters degree in computer science Engineering or a related quantitative field
Experience 10 years Enterprise Application development Proven track record of delivering AIML solutions in a production environment specifically within the BFSI or highly regulated sectors
• Tooling Deep expertise in Python, Lang Graph, Lang Chain Vector Databases and cloud native AI stacks Azure AI AWS Bedrock or GCP Vertex AI
• Architecture Strong foundation in microservices API design and enterprise security protocols

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