We're looking for a Senior Agentic AI Developer to join MindBridge's Applied AI team. You'll design, build, and operate production-grade LLM-powered agent systems that perform multi-step reasoning, tool use, and goal-oriented workflows. Reporting to the AI Architect, you'll own the full implementation lifecycle, from prototype to production, ensuring systems are robust, scalable, and secure.

Agentic AI Implementation

• Design and implement LLM-powered agentic systems that perform multi-step reasoning, tool use, and autonomous workflows
• Build agent pipelines using frameworks such as LangGraph, LangChain, AutoGen, or Semantic Kernel, with a focus on reliability and maintainability
• Implement robust patterns for RAG, memory, and planning, integrating vector databases and external tools so agents can act on real enterprise data
• Harden agent behavior with defensive coding: timeouts, retries, circuit breakers, and safe fallbacks for tool failures
• Implement guardrails and policies to mitigate prompt injection, data leakage, and unsafe actions
• Collaborate with the AI Architect to translate high-level designs into production-grade implementations

MLOps & Production Infrastructure

• Own the end-to-end lifecycle of agentic AI services: packaging, deployment, rollout, and ongoing maintenance
• Build CI/CD pipelines and infrastructure-as-code for safe, repeatable deployments and rollbacks
• Integrate with cloud platforms (AWS, GCP, Azure) and container orchestration (Docker, Kubernetes) to ensure scalability and cost efficiency
• Implement observability for agents: structured logging, tracing of tool calls, metrics for latency, cost, task success rate, and safety events
• Collaborate with platform and security teams to ensure compliance with governance, access control, and audit requirements

Software Engineering & Integration

• Develop and maintain backend services and APIs that expose agent capabilities to internal and external consumers
• Integrate agents with existing systems (databases, data warehouses, CRMs, SaaS tools) to build end-to-end workflows
• Ensure code quality through strong engineering practices: type hints, automated testing, code review, and documentation
• Implement security and multi-tenancy patterns around agent services, including authentication, data isolation, and rate-limiting
• Serve as the bridge between experimental prototypes and production systems

Required

• 5+ years of professional software engineering or AI/ML engineering experience, including building and operating production services
• Strong Python proficiency and familiarity with AI/ML and backend stacks (FastAPI, PyTorch, Hugging Face, or similar)
• Hands-on experience integrating LLMs into applications: prompt engineering, embeddings, RAG, or fine-tuning
• Practical experience with at least one agentic/LLM framework (LangGraph, LangChain, AutoGen, Semantic Kernel, or equivalents)
• Proven track record of shipping production systems on a major cloud provider (AWS, GCP, Azure) with containerization and orchestration
• Strong understanding of software engineering best practices: version control, automated testing, CI/CD, monitoring, and incident response

Preferred

• 2+ years working directly with LLM-based or agentic systems (multi-step agents, tool orchestration, autonomous workflows)
• Experience designing or operating multi-agent architectures (planner-executor-critic patterns, supervisor agents)
• Familiarity with vector databases (Pinecone, Weaviate, FAISS) and data platforms (warehouses, streaming)
• Exposure to AI governance and security (data privacy, access control, audit logging) in enterprise environments
• Experience with front-end or full-stack development (React, TypeScript) to collaborate on end-to-end user experiences
• Contributions to open-source agentic AI tools or internal frameworks

• You ship and own systems end-to-end, from code to production reliability
• You write clean, maintainable code that others can understand and extend
• You communicate clearly with cross-functional partners and document designs and trade-offs

You stay current with LLM and agentic AI developments, recommending tools that improve velocity and robustness

Pay Range

The expected base salary range for this position is $152,000 to $195,000 and may be eligible for bonus awards. The determination of an applicant’s base salary within this range is based on the individual’s location, skills, experience and competencies, and unique qualifications.

Requirements Contingent on Employment

• Fulfill requirements necessary to obtain and clear a full background check