Senior AI Developer – Investments & Agentic Platform

Invesco • Atlanta, GA

2d • Hybrid

About The Position

Invesco is seeking an experienced, hands-on Senior AI Developer to accelerate the adoption of artificial intelligence across Investments Technology. The role designs and builds enterprise AI capabilities supporting investment, research, risk, performance, and distribution functions. Working with architects, engineers, product owners, and business stakeholders, the developer delivers scalable AI solutions, establishes reusable patterns, and promotes modern AI engineering practices.

A major focus is leading implementation of a common semantic layer for Investments and Distribution data, developing AI agents for investment workflows, and helping teams adopt Spec-Driven Development and other AI-assisted engineering approaches. The role combines hands-on delivery, technical innovation, and technical leadership. It also involves evaluating emerging technologies, contributing to architecture and engineering standards, and sharing expertise with development teams.

The position is full-time and employee-based. Under Invesco’s workplace policy, employees are expected to work in an Invesco office at least four full days each week, as of October 1, 2025. The role is classified as exempt.

Requirements

• Strong software engineering experience with demonstrated delivery of enterprise applications.
• Hands-on experience designing and developing Generative AI, agentic AI, or machine learning solutions.
• Experience working with modern AI frameworks, orchestration platforms, and large language models.
• Strong understanding of enterprise application architecture and integration patterns.
• Experience working directly with business stakeholders to translate requirements into technical solutions.
• Excellent problem-solving, communication, and collaboration skills.
• Passion for continuous learning and applying emerging technologies.

Nice To Haves

• Experience in asset management, wealth management, investment management, research, trading, risk, or financial services.
• Experience developing semantic models, knowledge layers, metadata frameworks, or business taxonomies.
• Experience building enterprise AI agents and AI-enabled workflow solutions.
• Experience implementing AI governance, evaluation, and observability capabilities.
• Experience operating across Snowflake, AWS, and Microsoft AI ecosystems.
• Familiarity with Snowflake Cortex, Analyst, Search, or Cortex Code; AWS Bedrock or AgentCore; Azure Agent Foundry; Microsoft Copilot Studio; Anthropic Claude; LangGraph; LangChain; Strands; AutoGen; CrewAI; Model Context Protocol; multi-agent systems; or agent orchestration frameworks.
• Familiarity with retrieval-augmented generation, GraphRAG, enterprise search, semantic search, knowledge graphs, vector search and embeddings, or hybrid retrieval architectures.
• Familiarity with semantic modeling, business taxonomies, metadata management, ontology design, data catalogs, knowledge representation, or AI data governance.
• Familiarity with Spec-Driven Development, AI-assisted development, AI coding agents, LLM evaluation frameworks, prompt engineering, context engineering, AI observability, AI guardrails and safety controls, human-in-the-loop workflows, or LLMOps.

Responsibilities

• Build reusable AI platform components for multiple business capabilities.
• Integrate AI solutions with enterprise data platforms, model platforms, and business applications.
• Support governance, security, observability, and operational requirements for production AI solutions.
• Contribute to a scalable, maintainable AI ecosystem supporting experimentation and enterprise adoption.
• Lead design and implementation of a common semantic layer for Investments and Distribution use cases.
• Define semantic models, taxonomies, metadata structures, and business definitions to improve data accessibility and consistency.
• Work with data, engineering, and business teams to establish a governed, reusable data foundation for AI solutions.
• Support natural-language access to investment data through semantic and AI services.
• Design and develop AI agents supporting investment research, portfolio management, risk analysis, performance analytics, product intelligence, and distribution workflows.
• Build reusable agent frameworks, orchestration patterns, and integration approaches.
• Develop multi-step AI workflows combining structured and unstructured data sources.
• Establish approaches for agent evaluation, testing, observability, and continuous improvement.
• Track emerging AI technologies, frameworks, and industry trends and identify opportunities to apply them within Investments Technology.
• Evaluate tools and platforms through proof-of-concepts and practical experimentation.
• Contribute to AI architecture decisions and implementation standards.
• Mentor development teams and share knowledge through demonstrations, workshops, and documentation.
• Promote engineering best practices for scalable, secure, and maintainable AI solutions.
• Help introduce and scale Spec-Driven Development practices within Investments Technology.
• Use AI-assisted development tools to improve productivity and software quality.
• Contribute to standards for specification creation, automated testing, and AI-assisted delivery workflows.
• Develop reusable templates, reference implementations, and engineering patterns to accelerate solution delivery.

Benefits

• Flexible paid time off
• Hybrid work schedule
• 401(k) matching of 100% up to the first 6%, with a discretionary supplemental contribution
• Health and wellbeing benefits
• Parental leave benefits
• Employee stock purchase plan

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed