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Sr AI Software Developer

Job in Phoenix, Maricopa County, Arizona, 85003, USA
Listing for: Honeywell Aerospace US LLC
Full Time position
Listed on 2026-05-13
Job specializations:
  • Software Development
    AI Engineer, Cloud Engineer - Software, Machine Learning/ ML Engineer, Software Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Sr AI Software Developer

As a Sr AI Software Developer here at Honeywell, you will play a crucial role in the development of advanced AI solutions that drive business insights, enhance decision‑making processes, and empower AI solutions. Your expertise will help in critical data science development activities across all AI modalities (classic, Gen, and agentic) and data types (structured and unstructured).

You will report directly to our AI Director and you’ll work out of our Phoenix, AZ or Charlotte, NC location on a hybrid work schedule.

Key Responsibilities
  • Design and develop AI application services and middleware that connect classic ML models, GenAI/LLM systems, and agentic AI components to enterprise applications and workflows.
  • Build production‑grade RAG (Retrieval‑Augmented Generation) services, including chunking pipelines, embedding APIs, retrieval endpoints, caching, re‑ranking and content policy enforcement.
  • Develop agent tool adapters and integration layers enabling AI agents to safely perform actions (e.g., Snowflake queries, workflow triggers, system updates) using secure, controlled APIs.
  • Implement policy, safety, and guardrail middleware that enforces PII protection, content moderation, compliance rules and safe function execution for agentic systems.
  • Create event‑driven and asynchronous services using AWS‑native capabilities for agent orchestration, callbacks, monitoring and workflow routing.
  • Build microservices and SDKs that enable scalable, low‑latency interactions between AI models, vector databases and enterprise systems.
  • Collaborate with AI Architects, Platform Engineers, MLOps, Data Engineers and Data Scientists to ensure systems are reliable, secure, observable and aligned with best practices.
  • Implement robust testing frameworks for AI‑driven services including regression tests, guardrail tests, prompt and agent behaviour evaluations, and functional correctness checks.
  • Participate in code reviews, architectural discussions and continuous improvement initiatives to enhance the performance and reliability of AI‑powered applications.
Leadership Responsibilities
  • Lead the development of complex AI solutions to address specific business needs, ensuring scalability, efficiency and robustness.
  • Collaborate with cross‑functional teams to integrate AI solutions seamlessly into existing systems and processes.
  • Work directly with product managers and business leaders to understand requirements and align AI initiatives with overall business objectives.
  • Lead the end‑to‑end AI development lifecycle, including project planning, resource allocation and monitoring progress.
  • Provide mentorship and guidance to AI engineers, fostering a culture of continuous learning, innovation and technical excellence.
Qualifications
  • Bachelor’s degree from an accredited institution in a technical discipline such as sciences, technology, engineering or mathematics.
  • 5 or more years of experience in software development, ideally building backend, middleware or distributed systems.
  • Strong proficiency in Python or Java/Type Script, with hands‑on experience building REST APIs, event‑driven services and microservices.
  • Experience working with AI/ML application patterns, including RAG, vector stores, prompt orchestration and model/LLM integration.
  • Practical experience deploying applications on AWS using services such as Lambda, API Gateway, ECS/EKS, Step Functions, SQS/SNS or Dynamo

    DB.
  • Familiarity with Databricks (Delta Lake, SQL Warehouses, Model Serving, Vector Search) and integration patterns for data access and processing.
  • Experience building data or AI workflows that interact with Snowflake, including secure queries, role‑based access and performance optimization.
  • Experience working with Dataiku APIs or automation for data workflows, scoring endpoints or integration into AI services.
  • Strong understanding of API design, authentication/authorization, secure coding practices and system observability.
  • Ability to collaborate in an agile, cross‑functional environment with platform engineering, MLOps, data engineering and data science teams.
Preferred Qualifications
  • Experience building integrations for agentic AI systems, including tool…
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