Lead Application Developer

This position is with a client of Phyton Talent Advisors

We are pioneering a new class of agentic AI systems—intelligent, adaptive platforms that continuously learn from firm knowledge and act responsibly to enhance decision‑making and client outcomes. These systems will enable real‑time knowledge orchestration and insight generation across the enterprise, amplifying the collective intelligence of our advisors, associates, and business units.

As part of the Agentic AI Data Science team, you will architect and deliver scalable, secure, and high‑performance agentic solutions using and extending frameworks such as Strands, CrewAI, Lang Graph, Agent Core, and related technologies. You will help design the foundational infrastructure that allows these systems to learn safely, adapt in real time, and deliver measurable value—all while operating within the disciplined, client‑first culture that defines us.

This is a hands‑on engineering role requiring exceptional technical depth, strong design judgment, and a passion for building systems that are both innovative and enduring. You’ll collaborate across engineering, data, and governance teams to ensure every solution balances speed, integrity, and long‑term impact.

• Architect and Build Agentic Systems:
  Design and implement agentic AI architectures capable of reasoning, planning, and self‑adaptation within firm‑approved security and compliance boundaries.
• Leverage and Extend Frameworks:
  Utilize and enhance frameworks such as Strands, CrewAI, Lang Graph, and Agent Core to create standardized, reusable components that accelerate agentic development across teams.
• Cloud Engineering:
  Develop secure, resilient, and scalable cloud‑native solutions using AWS services (Lambda, ECS, S3, API Gateway, Sage Maker, Bedrock, etc.) to support production‑grade AI operations.
• Monitoring and Evaluation:
  Implement metrics, tracing, and evaluation pipelines that ensure transparency, reliability, and continuous improvement in agentic behavior.
• Integration and Governance:
  Collaborate with security, risk, and compliance to embed governance, auditability, and ethical safeguards into all systems.
• Collaboration:
  
  Partner with data science, enterprise architecture, and application engineering teams to integrate agentic capabilities into firm platforms.
• Innovation Leadership:
  Research, test, and recommend new frameworks and patterns that responsibly advance the firm’s AI capabilities.
• Ownership:
  Drive full lifecycle delivery—from technical design through deployment and iteration—maintaining high standards of reliability and documentation.

Technical Strengths:

• Proficiency in Python (with experience in Type Script, Go, or Java a plus).
• Solid understanding of AWS architecture and services—deployment, monitoring, security, and cost optimization.
• Familiarity with agentic or LLM frameworks such as Strands, CrewAI, Lang Graph, Agent Core, or similar.
• Experience with retrieval systems, vector databases, embeddings, and orchestration frameworks.
• Strong grounding in secure API design, data modeling, and CI/CD automation.
• Proven record of writing clean, testable, production‑grade code.

Mindset: Deep curiosity, bias toward execution, and respect for precision and reliability.

Financial services experience preferred but not required.

Competencies and Behaviors:

• Analytical Thinking:
  Deconstruct complex technical and business challenges into clear, scalable solutions.
• Communication:
  Translate advanced technical concepts into shared understanding across business, technology, and risk partners.
• Judgment:
  Balance innovation with security, compliance, and long‑term maintainability.
• Technical Mastery:
  Maintain and expand expertise in agentic AI, cloud engineering, and software craftsmanship.
• Collaboration:
  
  Work cross‑functionally with integrity and respect, ensuring outcomes align with the firm’s mission and standards.
• Client Focus and Integrity:
  Make decisions grounded in what best serves clients and the firm’s long‑term stability—acting with transparency and accountability.

Bachelor’s degree in Computer Science, Engineering, or related field; equivalent experience considered.

Experience: 5+ years of professional software engineering, with demonstrated success in building scalable distributed systems or AI‑powered platforms.