AI Engineer

Job title: AI Solution Developer Location: Hyderabad Opella is the self-care challenger with the purest and third-largest portfolio in the Over-The-Counter (OTC) & Vitamins, Minerals & Supplements (VMS) market globally. Our mission is to bring health in people’s hands by making self-care as simple as it should be. For half a billion consumers worldwide – and counting. At the core of this mission is our 100 loved brands, our 11,000-strong global team, our 13 best-in-class manufacturing sites and 4 specialized science and innovation development centers. Headquartered in France, Opella is the proud maker of many of the world’s most loved brands, including Allegra, Buscopan, Doliprane, Dulcolax, Enterogermina, Essentiale and Mucosolvan. As a globally certified B Corp company, we are active players in the journey towards healthier people and planet. Find out more about our mission at www.opella.com. About the job: The AI Solution Developer builds, integrates, and operates AI agents that act directly within Opella’s Manufacturing & Supply (M&S) core systems — Manufacturing Execution Systems (MES), Quality Management Systems (QMS), and Enterprise Resource Planning (ERP). Where analytics and copilots advise, this role makes agents act: designing, deploying, and running production-grade agentic workflows that execute tasks, trigger transactions, and close the loop between insight and operation across Supply Chain, Manufacturing, and Quality. This is a hands-on, technical-and-business hybrid role at the heart of the MS.AI Factory. The ideal candidate combines strong software and AI engineering skills with deep familiarity of manufacturing and supply chain systems, and thrives in a Forward Deployed Engineer (FDE) model — embedded with business teams, shipping working agents into live operations rather than slideware. Main Responsibilities Agent Development: Design, build, and integrate AI agents that act within MES, QMS, and ERP — so agents execute tasks and transactions, not just generate recommendations. System Integration: Connect agents to enterprise systems (SAP, MES, QMS, LIMS) through APIs, MCP-based integrations, and event-driven workflows, ensuring safe, auditable, and reversible actions. End-to-End Delivery: Own the full lifecycle from proof-of-concept to production and operations — experimentation → productionization → monitoring and maintenance. Agentic AI & GenAI: Build RAG workflows, multi-agent orchestrations, and LLM-powered solutions using modern agentic frameworks, vector databases, embeddings, and prompt engineering. Forward Deployed Engineering: Embed with Supply Chain, Manufacturing, and Quality stakeholders to identify high-value use cases and ship working agents directly into their workflows. Reliability & Guardrails: Establish data hygiene, validation, human-in-the-loop controls, and observability so autonomous actions are safe, GxP-aware, compliant, and trustworthy. Operate & Scale: Run deployed agents in production, monitor performance, cost, and drift, and continuously improve reliability and measurable business impact. Enablement: Partner with Citizen Developers and AI Champions, turning proven agents into reusable, scalable patterns across the M&S organization. About you: Required Skills & Qualifications Software & AI Engineering: Strong hands-on development skills (Python), with production-ready software engineering practices — OOP, coding standards, version control, testing, and CI/CD. Agentic AI & GenAI: Experience designing and deploying LLM-powered and agentic solutions (RAG, autonomous and multi-agent systems), with MCP-based integrations, embeddings, vector databases, and prompt engineering. System Integration: Proven ability to integrate solutions directly into enterprise systems via APIs; exposure to MES / QMS / ERP (SAP) and manufacturing / supply chain data. MLOps / AgentOps: Experience operationalizing models and agents — automated build / test / deploy, monitoring, and observability (e.g., MLflow, Kubeflow or similar; GitLab CI/CD, Azure DevOps, Jenkins). Cloud & Data: Comfortable in cloud and high-performance environments (Azure, AWS, GCP, Databricks, Snowflake) and building data pipelines. Business Understanding: Familiarity with Supply Chain, Manufacturing, and Quality processes and KPIs, and the ability to translate business problems into deployable agents. Experience: [Add required years] of hands-on experience building and deploying production AI / software solutions; life-scie…