Software Engr II

Honeywell
Hyderabad
Workplace: OnsiteFull timeFunction: Software EngineeringSkills: ["Collaboration","Mentoring"]

Design, develop, and maintain production-grade Generative AI and Agentic AI solutions for enterprise applications. Build autonomous agents with reasoning, planning, tool use, multi-agent collaboration, and HITL controls. Develop advanced RAG pipelines using vector databases, embeddings, and enterprise knowledge retrieval. Orchestrate resilient AI workflows (self-correction, failure recovery, debugging loops) and deploy/monitor models across on-prem, hybrid, and public cloud environments (Azure/AWS/GCP).

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FursaFursa
Honeywell
Honeywell
1 day ago

Software Engr II

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Source: Company careers pageValidated by: Fursa AI
Last checked: 3 hours agoStatus: Live
Reposted: similar role first listed 6 months ago

Job Summary

Design, develop, and maintain production-grade Generative AI and Agentic AI solutions for enterprise applications. Build autonomous agents with reasoning, planning, tool use, multi-agent collaboration, and HITL controls. Develop advanced RAG pipelines using vector databases, embeddings, and enterprise knowledge retrieval. Orchestrate resilient AI workflows (self-correction, failure recovery, debugging loops) and deploy/monitor models across on-prem, hybrid, and public cloud environments (Azure/AWS/GCP).
Location: Hyderabad
Workplace: Onsite
Employment Type: Full time
Job Function: Software Engineering
Seniority: Mid level

Key Responsibilities

  • •Design and develop production-grade Generative AI and Agentic AI applications.
  • •Build autonomous and semi-autonomous AI agents that reason, plan, use tools, and collaborate with other agents.
  • •Develop multi-step reasoning workflows combining deterministic business logic with LLM-generated reasoning, including short-term/long-term memory architectures.
  • •Implement resilient AI workflows with self-correction, failure recovery, debugging loops, and Human-in-the-Loop approval controls.
  • •Ensure production readiness by integrating LLMs/VLMs with enterprise APIs and databases, then monitoring, testing, performance optimization, and governance controls.

Key Requirements

  • •Strong proficiency in Python and experience designing and implementing enterprise-grade software solutions.
  • •Hands-on experience building agentic AI using agent orchestration frameworks such as LangGraph or OpenAI Agents SDK, including planning, reflection, and tool use.
  • •Experience designing advanced RAG architectures, including vector databases, embeddings, semantic search, and enterprise knowledge retrieval systems.
  • •Hands-on experience deploying Generative AI solutions across on-premises, hybrid architectures, and public cloud platforms such as Microsoft Azure, AWS, or GCP.
  • •Experience with Docker and Kubernetes/containerized deployments, plus familiarity with model evaluation/observability and AI workflow governance.
Education:
Skills:CollaborationMentoring
Tech Stack:PythonGenerative AIAgentic AILarge Language Models (LLMs)Vision Language Models (VLMs)LangGraphOpenAI Agents SDKFunction callingStructured outputsPrompt engineeringContext window managementEmbeddingsRetrieval-Augmented Generation (RAG)Vector databasesSemantic searchHuman-in-the-Loop (HITL)Microsoft AzureAWSGoogle Cloud Platform (GCP)Docker

Company Brief

Honeywell
Global diversified technology and manufacturing company providing aerospace systems, building technologies, performance materials, and safety & productivity solutions for industrial, commercial, and consumer markets.
Industry: Conglomerates & Holding Companies
Company Size: Enterprise (1,001+ employees)
Revenue: USD 25B to 50B
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Charlotte, United States
Founded: 1906
Glassdoor
Glassdoor: 3.8
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