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Senior AI Solutions Developer

Inabia Software & Consulting Inc.

Rutherford, NJ • 9/15/2026

Job Description

Job Description
We are seeking an experienced AI/LLM Software Engineerto design, develop, and deploy enterprise-grade AI applications, assistants, agents, and intelligent workflows. The ideal candidate will have strong hands-on Python and software engineeringexperience combined with practical expertise in LLMs, RAG, agentic AI, orchestration frameworks, tool integration, and AI observability.
This is a highly collaborative, stakeholder-facing role requiring the ability to translate business requirements into secure, scalable, and production-ready AI solutions.
Key Responsibilities
  • Design and develop enterprise AI/LLM applications, assistants, agents, and intelligent workflows.
  • Build scalable and production-ready solutions using Pythonand modern software engineering practices.
  • Develop agentic AI workflowsusing frameworks such as LangGraphor similar orchestration technologies.
  • Implement tool integrations using MCP/FastMCPor comparable protocols and frameworks.
  • Build and integrate REST APIs, enterprise systems, databases, and SQL-based solutions.
  • Develop RAG (Retrieval-Augmented Generation)solutions using structured and unstructured data sources.
  • Design secure data-access patterns incorporating authentication, authorization, and enterprise security requirements.
  • Implement AI evaluation, monitoring, tracing, and observability using tools such as LangSmith, Weights & Biases (W&B), OpenTelemetry, or similar platforms.
  • Establish mechanisms to evaluate LLM accuracy, reliability, latency, cost, and overall application performance.
  • Incorporate Human-in-the-Loop (HITL)processes into AI workflows where appropriate.
  • Apply principles of AI governance, responsible AI, privacy, security, and compliancethroughout the development lifecycle.
  • Collaborate directly with business stakeholders, product teams, architects, and engineering teams to identify opportunities and deliver AI solutions.
  • Act as a forward-deployed engineer, working closely with stakeholders to understand problems, prototype solutions, gather feedback, and rapidly iterate.
  • Troubleshoot, optimize, and continuously improve AI applications in production environments.
  • Contribute to technical documentation, architecture decisions, development standards, and best practices.
Required Qualifications
  • 5–8 years of professional software engineering experience.
  • Strong hands-on experience with Pythonand software development.
  • Demonstrated experience building AI/LLM-powered applicationsin enterprise or production environments.
  • Experience developing AI assistants, agents, agentic workflows, or LLM applications.
  • Hands-on experience with MCP/FastMCPor similar tool-integration technologies.
  • Experience with LangGraphor comparable AI/agent orchestration frameworks.
  • Strong understanding of APIs, SQL, databases, and enterprise system integration.
  • Experience implementing RAG solutionsusing structured and/or unstructured data.
  • Experience with LLM evaluation, monitoring, tracing, or observability tools such as LangSmith, W&B, OpenTelemetry, or similar.
  • Understanding of authentication, authorization, secure data access, and enterprise security practices.
  • Strong understanding of AI governance, responsible AI, privacy, security, and Human-in-the-Loop concepts.
  • Excellent communication and stakeholder-management skills.
  • Ability to work directly with customers/business stakeholders in a forward-deployed engineeringcapacity.
Preferred Qualifications
  • Experience working with major LLM platforms and APIs such as OpenAI, Azure OpenAI, Anthropic, or similar.
  • Experience with vector databases, embeddings, semantic search, and retrieval pipelines.
  • Experience deploying AI applications in cloud environments such as Azure, AWS, or GCP.
  • Familiarity with CI/CD, Git, containers, and modern DevOps practices.
  • Experience building enterprise-grade AI solutions with strong emphasis on security, scalability, reliability, and governance.
  • Experience working in consulting, professional services, or customer-facing engineering environments.
Key Technologies
Python | LLMs | Generative AI | AI Agents | AI Assistants | MCP / FastMCP | LangGraph | RAG | APIs | SQL | Databases | LangSmith | W&B | OpenTelemetry | Authentication | Authorization | AI Governance | Responsible AI | HITL | Enterprise Integration

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