Python and Gen AI Engineer - Lead Software Engineer

About this role:

• Wells Fargo is seeking a Lead Software Engineer.
• The COO Technology group provides technology services for the Chief Operating Office. This includesoperations, control executives, strategic execution, business continuity and resiliency, data solutions andservices, regulatory relations, customer experience, enterprise shared services, supply chain management, andthe corporate properties group. COO Technology provides technology solutions and manages application
  portfolios for these groups to support modernization and optimization.
• Within COO Technology we are seeking a Lead Software Engineer - Generative AI - whose role is essential forexecuting strategic vision and driving concrete results
• TheGenerative AI Teamis building next-generation autonomous workflow automation that transforms business processes through intelligent agent orchestration, knowledge extraction, and real-time observability. We're seeking aLead Software Engineer - Generative AIto architect complex agentic systems, build scalable ETL pipelines, and mentor team members on GenAI best practices.
• Our platform's unique value lies in:
  • Agentic AI Orchestration: Multi-agent workflows using Google ADK (Sequential, Parallel, Loop patterns) with built-in validation
  • Modern ETL Pipelines: Data transformation for video content clustering and knowledge extraction
  • Knowledge Graph Intelligence: Graph databases with semantic embeddings for intelligent task replication
  • LLM Framework Integration: Google Gemini, LiteLLM routing, LangChain/LlamaIndex orchestration with prompt caching and function calling
  • Observability-First Design: Real-time metrics, correlation tracking, and audit trails via OpenTelemetry, Splunk, or Arize Phoenix
  • In this role, you'll own end-to-end implementation of agentic AI features, establish patterns for knowledge extraction ETL pipelines, and help define technical standards across the team.

In this role, you will:

• Lead moderately complex initiatives and deliverables within technical domain environments
• Contribute to large scale planning of strategies
• Design, code, test, debug, and document for projects and programs associated with technology domain, including upgrades and deployments
• Review moderately complex technical challenges that require an in-depth evaluation of technologies and procedures
• Resolve moderately complex issues and lead a team to meet existing client needs or potential new clients needs while leveraging solid understanding of the function, policies, procedures, or compliance requirements
• Collaborate and consult with peers, colleagues, and mid-level managers to resolve technical challenges and achieve goals
• Lead projects and act as an escalation point, provide guidance and direction to less experienced staff

Required Qualifications:

• 5+ years of Software Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education

Additional Required Qualification:

• 5+ yearsof Software Engineering experience with2+ yearsin GenAI/AI systems implementation
• 2+ yearshands-on experience withPython 3.12+and modern AI/ML frameworks:
• LLM Frameworks: LangChain, LlamaIndex, or AutoGen
• Agent Platforms: Google ADK, Crew AI, or similar
• LLM APIs: Google Gemini, OpenAI, Claude, or LiteLLM
• 2+ yearsdesigning and implementingmulti-agent systemsor agentic AI workflows
• 2+ yearsdirect hands-on experience withLarge Language Models: LLM selection, prompt engineering, model routing, parameter tuning, function calling
• ExperiencewithETL pipeline development: data transformation, validation, orchestration
• Experiencewithsemantic search and embeddings: vector databases (Pinecone, Weaviate, ChromaDB), embedding models, similarity search
• Experiencewithclustering algorithms(K-means, DBSCAN, hierarchical clustering) and pattern recognition
• Cloud platform experience (Google Cloud, AWS, or Azure) with focus on AI/ML services
• 3+ yearswithCI/CD/DevOps tools: Git, automated testing, deployment pipelines, container basics
• Experience withasync Python patterns: asyncio, async/await, concurrent patterns
• Strong experience withdatabase design: SQL, NoSQL, graph databases, repository patterns, transaction management
• Strong problem-solving skills with attention to detail and quality

Desired Qualifications:

• Software Engineering
  • Python 3.12+ with async/await, type hints, modern frameworks
• Database Design: SQL, NoSQL, graph databases, transaction management, ORM frameworks
• Observability & DevOps
  • Observability Architecture: OpenTelemetry, Splunk, Arize Phoenix, Prometheus metrics
  • CI/CD & Deployment: Automated testing, deployment pipelines, container orchestration basics
  • Cloud Platforms: Google Cloud, AWS, or Azure (AI/ML services focus)
• Quality & Security
  • Test-Driven Development: Contract testing, integration testing, unit testing
  • Secure Development: Data redaction, secure credential management, audit logging
  • Performance Optimization: Inference tuning, ETL performance profiling, cost optimization
• Preferred Experience Level
  • 3-5 yearsat mid-level positions (Senior IC roles) with architecture exposure
  • Deep technical expertisewith ability to own complex features end-to-end
  • Self-sufficientin implementation with minimal guidance
  • Mentorship capabilitywith proven track record of helping junior engineers grow
  • Communication skillsto explain complex concepts to technical and non-technical stakeholders

Job Expectations:

• Technical Implementation & Ownership
  • Design and implement multi-agent workflow systems usingGoogle ADKsupporting complex business processes (sequential execution, parallel branches, iterative loops)
  • Own end-to-end implementation of GenAI features, from architecture to production deployment
  • Build robust agentic AI systems usingPython 3.12+, Google ADK, LangChain/LlamaIndex, and modern frameworks with strong testing discipline
  • Architect ETL pipelines usingLLMsfor transforming raw video content into structured knowledge representations
  • Implementsemantic search and clusteringusing Scikit-learn, FAISS, or Pinecone for workflow pattern identification
  • Buildknowledge graph systems for capturing task dependencies and semantic relationships
  • OptimizeLLM inferencewith prompt caching, function calling, batch processing, and LiteLLM routing strategies
  • Implement secure CI/CD pipelines for AI model deployment with comprehensive automated testing for agent behavior validation
  • Architect and integrate observability instrumentation into agent execution lifecycle
  • Optimize AI inference performance, manage costs, and tune model parameters (temperature, top_p, seed) for production workloads
• ETL Pipeline & Data Engineering
  • Design scalable ETL pipelines for video metadata extraction, clustering, and knowledge graph construction
  • Buildfeature engineering pipelinesfor embedding generation
  • Implementstreaming data pipelineswith Apache Kafka or Redis for real-time knowledge updates
• LLM Integration & Prompt Engineering
  • ArchitectLLM routing systemsusing LiteLLM with fallback patterns and cost optimization
  • Implementprompt caching strategiesfor efficient API usage across multi-turn conversations
  • Buildfunction calling frameworksfor agent tool invocation with proper type validation
  • IntegrateRAG (Retrieval Augmented Generation)systems with knowledge graphs and vector databases
  • Implementchain-of-thoughtprompting andmulti-turn conversationmanagement with LLMs
  • Designoutput validation pipelinesusing structured outputs and LLM guardrails
• Architecture & Design Decisions
  • Lead technical design discussions for agentic AI features and knowledge extraction pipelines
  • Evaluate and recommend AI frameworks: Google ADK, AutoGen, LangChain, LlamaIndex, Crew AI
  • Design scalable database schemas and knowledge graph models
  • Contribute to architectural decisions ensuring reliability, security, and scalability

Posting End Date:
3 Feb 2026
*Job posting may come down early due to volume of applicants.
We Value Equal Opportunity
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