Job Overview Honeywell is hiring an AI Engineer II in Hyderabad, Telangana, for a full-time, on-site engineering role focused on production-grade Generative AI and Agentic AI solutions. The position involves building intelligent enterprise applications that can reason, plan, use tools, collaborate with other agents, and operate within complex business environments. The role combines software engineering, machine learning, large language models, retrieval systems, cloud deployment, and AI workflow automation. The selected engineer will work with product, engineering, and domain teams to turn business requirements into scalable AI systems. The position also includes technical oversight, reviewing work performed by team members, managing project execution, and mentoring junior colleagues. Key Responsibilities The AI Engineer will design, develop, deploy, and scale enterprise Generative AI and Agentic AI applications. This includes creating autonomous and semi-autonomous agents that can plan tasks, call tools, reason through problems, and collaborate with other agents. A significant part of the role involves building advanced Retrieval-Augmented Generation pipelines using vector databases, embeddings, semantic search, and enterprise information sources. Engineers will also create multi-step workflows that combine deterministic business rules with LLM-generated reasoning. The position includes designing memory architectures that allow AI systems to maintain useful short-term and long-term context. AI workflows should also be resilient, with mechanisms for self-correction, failure recovery, automated debugging, and Human-in-the-Loop controls. You will integrate LLMs, Vision Language Models, enterprise APIs, databases, external tools, and business applications into broader agent ecosystems. Solutions may be deployed across public cloud, hybrid, and on-premises environments. Production readiness is another important responsibility. Engineers will contribute to monitoring, testing, performance optimization, governance, and operational controls. The role also includes supervising and reviewing team activities, providing clear direction, managing end-to-end delivery for internal or external clients, and supporting the professional development of junior team members. Required Skills Strong Python programming ability and experience developing enterprise-grade software are essential. Candidates should understand software engineering practices such as version control, testing, maintainable development, and CI/CD. Hands-on experience with Agentic AI orchestration frameworks such as LangGraph or the OpenAI Agents SDK is relevant. Candidates should understand agent design patterns including reflection, tool use, planning, and multi-agent collaboration. Practical knowledge of function calling, structured outputs, prompt engineering, and context-window management is also required. Candidates should understand the capabilities and limitations of modern foundation models and know how to optimize AI applications around those constraints. Preferred Skills Experience with regulated enterprise environments is useful, especially where AI governance, security, privacy, auditability, and responsible AI practices are important. Experience developing multi-agent systems for business or operational workflows is also valuable. Knowledge of model evaluation, observability, AI performance monitoring, MLOps, and operationalization of machine learning workloads can strengthen an application. Candidates with experience designing self-healing workflows, automated debugging systems, approval controls, and quality checkpoints are particularly relevant to the technical scope. Education A Bachelor's or master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical discipline is required according to the job description. Experience The provided job description does not specify a numerical experience requirement. Instead, it emphasizes hands-on production experience with Generative AI, Agentic AI, LLM applications, RAG architectures, enterprise software, cloud deployment, and AI workflow engineering. Candidates should be able to demonstrate practical delivery of production-oriented AI systems rather than only academic familiarity. Required Technologies The core technology landscape includes Python, Generative AI, Agentic AI, Large Language Models, Vision Language Models, embedding models, LangGraph, OpenAI Agents SDK, Retrieval-Augmented Generation, vector databases, semantic search, enterprise APIs, Docker, Kubernetes, Microsoft Azure, AWS, Google Cloud Platform, CI/CD, distributed systems, and containerized deployments. The machine learning scope includes classification, regression, clustering, decision trees, neural networks, Support Vector Machines, anomaly detection, recommender systems, pattern discovery, text mining, statistical modeling, and predictive analytics. Soft Skills The position requires strong communication, leadership, mentoring, collaboration, analytical thinking, and problem-solving skills. Engineers should be comfortable working with product specialists, developers, and domain experts to translate business requirements into technical solutions. The role also requires ownership and clear execution because the engineer may oversee tasks, manage project activities, guide team members, and contribute to delivery commitments. A willingness to learn evolving AI technologies is important in a rapidly changing technical environment. Benefits of Working in this Role This role provides exposure to production AI engineering across Generative AI, Agentic AI, RAG, cloud infrastructure, machine learning, and enterprise automation. The position also offers opportunities to develop leadership and mentoring skills while working on business-oriented AI systems. Honeywell states that its employee offering includes opportunities related to professional growth and development. Specific benefits beyond those stated in the job posting should be confirmed during the hiring process. Work Mode This position is explicitly listed as On-site. The job is based at Honeywell's location in Nanakramguda, Hyderabad, Telangana. Location The role is located in Hyderabad, Telangana, India. Hyderabad is a major technology center with strong activity across software engineering, artificial intelligence, cloud computing, data science, enterprise applications, and automation. The location provides access to a broad technology ecosystem for professionals working in AI and software engineering. Who Should Apply This opportunity is suitable for AI engineers and software professionals with practical experience building production-oriented Generative AI or Agentic AI applications. Candidates should be strong in Python and comfortable with LLMs, RAG, AI orchestration, cloud platforms, containers, and machine learning. Applicants who can demonstrate experience with agent workflows, enterprise integrations, vector databases, model evaluation, AI observability, or MLOps should consider applying. Candidates should also be comfortable mentoring junior engineers and collaborating across technical and business teams. Career Growth The position can support growth toward senior AI engineering, machine learning engineering, AI architecture, MLOps, AI platform engineering, or technical leadership roles. Experience across agentic systems, RAG, cloud deployment, enterprise AI governance, and AI infrastructure can help build a broad production AI engineering profile. Application Advice Build your resume around real AI systems and measurable engineering outcomes. Highlight production work involving Python, LLMs, RAG, agent frameworks, vector databases, cloud platforms, Docker, Kubernetes, or MLOps. Describe the problem you solved, the architecture you selected, how the system was evaluated, and how you handled reliability or performance concerns. If you have built multi-agent workflows, self-healing processes, tool-using agents, enterprise integrations, or model evaluation frameworks, explain those projects clearly. Also mention relevant leadership, mentoring, or delivery responsibilities. Avoid listing technologies without showing how you used them in practical projects. Apply now through SoftoJobs to explore this opportunity.