Job Description

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 The

Generative AI Team

is building next-generation autonomous workflow automation that transforms business processes through intelligent agent orchestration, knowledge extraction, and real-time observability. We're seeking a

Lead Software Engineer - Generative AI

to 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 years

at mid-level positions (Senior IC roles) with architecture exposure
+

Deep technical expertise

with ability to own complex features end-to-end
+

Self-sufficient

in implementation with minimal guidance
+

Mentorship capability

with proven track record of helping junior engineers grow
+

Communication skills

to explain complex concepts to technical and non-technical stakeholders

Job Expectations:

Technical Implementation & Ownership

+ Design and implement multi-agent workflow systems using

Google ADK

supporting 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 using

Python 3.12+

, Google ADK, LangChain/LlamaIndex, and modern frameworks with strong testing discipline
+ Architect ETL pipelines using

LLMs

for transforming raw video content into structured knowledge representations
+ Implement

semantic search and clustering

using Scikit-learn, FAISS, or Pinecone for workflow pattern identification
+ Build

knowledge graph systems

for capturing task dependencies and semantic relationships
+ Optimize

LLM inference

with 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
+ Build

feature engineering pipelines

for embedding generation
+ Implement

streaming data pipelines

with Apache Kafka or Redis for real-time knowledge updates

LLM Integration & Prompt Engineering

+ Architect

LLM routing systems

using LiteLLM with fallback patterns and cost optimization
+ Implement

prompt caching strategies

for efficient API usage across multi-turn conversations
+ Build

function calling frameworks

for agent tool invocation with proper type validation
+ Integrate

RAG (Retrieval Augmented Generation)

systems with knowledge graphs and vector databases
+ Implement

chain-of-thought

prompting and

multi-turn conversation

management with LLMs
+ Design

output validation pipelines

using 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

Wells Fargo is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other legally protected characteristic.



Employees support our focus on building strong customer relationships balanced with a strong risk mitigating and compliance-driven culture which firmly establishes those disciplines as critical to the success of our customers and company. They are accountable for execution of all applicable risk programs (Credit, Market, Financial Crimes, Operational, Regulatory Compliance), which includes effectively following and adhering to applicable Wells Fargo policies and procedures, appropriately fulfilling risk and compliance obligations, timely and effective escalation and remediation of issues, and making sound risk decisions. There is emphasis on proactive monitoring, governance, risk identification and escalation, as well as making sound risk decisions commensurate with the business unit's risk appetite and all risk and compliance program requirements.



Candidates applying to job openings posted in Canada: Applications for employment are encouraged from all qualified candidates, including women, persons with disabilities, aboriginal peoples and visible minorities. Accommodation for applicants with disabilities is available upon request in connection with the recruitment process.

Applicants with Disabilities

To request a medical accommodation during the application or interview process, visit Disability Inclusion at Wells Fargo .

Drug and Alcohol Policy

Wells Fargo maintains a drug free workplace. Please see our Drug and Alcohol Policy to learn more.

Wells Fargo Recruitment and Hiring Requirements:

a. Third-Party recordings are prohibited unless authorized by Wells Fargo.



b. Wells Fargo requires you to directly represent your own experiences during the recruiting and hiring process.