Agentic AI - Lead Application Developer

Noblesoft Solutions; Saint Petersburg (FL); Hybrid; USD 100,000 - 130,000; Full time

Job summary

Noblesoft Solutions is seeking a skilled individual to architect and build agentic systems. This hybrid role in St. Petersburg, FL involves designing AI solutions, leveraging AWS technologies, and collaborating with cross-functional teams.

The ideal candidate will have a strong background in Python and AWS, and experience with agentic frameworks. Candidates with financial services experience are preferred but not required. Join us to help innovate the next generation of AI capabilities.

Responsibilities

• Design and implement agentic AI architectures.
• Utilize and enhance frameworks for agentic development.
• Develop secure, scalable cloud-native solutions using AWS.
• Implement metrics for transparency and evaluation.
• Collaborate on governance and compliance integration.
• Lead innovation and research in AI frameworks.

Skills

Proficiency in Python

AWS architecture and services

Agentic frameworks experience

Retrieval systems and vector databases

Secure API design

Testable production-grade code

Model Context Protocol design

Agent and LLM evaluation

Amazon Bedrock experience

Containerization and orchestration

Terraform for IaC deployments

OpenTelemetry for observability

Job description

Contract Duration: 12+ Months

Location: St. Petersburg, FL (Hybrid for 3 days)

Responsibilities

• 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, LangGraph, and AgentCore 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, SageMaker, 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
• Other responsibilities as assigned

Skills

• Proficiency in Python (with experience in TypeScript, 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, LangGraph, Agent Core, or similar
• Experience with retrieval systems, vector databases, embeddings, and orchestration framework
• Strong grounding in secure API design, data modeling, and CI/CD automation
• Proven record of writing clean, testable, production‑grade code
• Experience designing tool/function‑calling integrations and Model Context Protocol (MCP) servers and connectors
• Strong prompt and context engineering, including agent memory, state, and session/context management
• Experience with agent and LLM evaluation, guardrails, and safety controls—hallucination mitigation, content filtering, and human‑in‑the‑loop oversight
• Hands‑on experience with foundation models via Amazon Bedrock (e.g., Anthropic Claude), including model selection and prompt/parameter tuning for latency and cost
• Familiarity with multi‑agent orchestration and workflow design—planning, task decomposition, routing, tool use, and error handling
• Experience with containerization and orchestration (Docker, Kubernetes) for deploying scalable, resilient services
• A good understanding of scalable, reliable, and reusable Agent Harnesse
• Knowledge of Terraform for IaC deployments; hands‑on experience with Terraform is a plus
• OpenTelemetry for Dynatrace and Observability
• Experience with agent performance tuning and cost optimization
• Experience with time‑boxed A2A and Swarm/Crew Agentic solutions
• Deploying large language models on‑prem
• Experience with fine‑tuning LLMs – nice to have
• Mindset: Deep curiosity, bias toward execution, and respect for precision and reliability
• Financial services experience preferred but not required