{"id":1252182,"url":"https://alion.io/job/nisum-platform-engineer","title":"Platform Engineer","company":{"id":1850626,"name":"Nisum","domain":"nisum.com","url":"https://alion.io/company/nisum","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"DevOps","role_family":"DevOps","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Hyderabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16000,"max_usd":37000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":42},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Azure","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Google ADK","optional":false},{"name":"Kubernetes","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"LLMOps","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Platform Engineering","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Rest API","optional":false},{"name":"Tool Use","optional":false}],"status":"live","first_seen_at":"2026-09-15T11:48:46Z","employer_posted_date":null,"last_verified_at":"2026-09-15T11:48:46Z","board_verified":false,"closed_at":null,"days_open":15,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":15},"description":"Job Description :\n\nWhat You'll Do :\n\n- Deploy, scale, and operate ML and Generative AI systems in cloud-based production environments (Azure preferred).\n\n- Build and manage enterprise-grade RAG applications using embeddings, vector search, and retrieval pipelines.\n\n- Implement and operationalise agentic AI workflows with tool use, leveraging frameworks such as Lang Chain and Lang Graph.\n\n- Develop reusable infrastructure and orchestration for GenAI systems using Model Context Protocol (MCP) and AI Development Kit (ADK).\n\n- Design and implement model and agent serving architectures, including APIs, batch inference, and real-time workflows.\n\n- Establish best practices for observability, monitoring, evaluation, and governance of GenAI pipelines in production.\n\n- Integrate AI solutions into business workflows in collaboration with data engineering, application teams, and stakeholders.\n\n- Drive adoption of MLOps / LLM Ops practices, including CI/CD automation, versioning, testing, and lifecycle management.\n\n- Ensure security, compliance, reliability, and cost optimisation of AI services deployed at scale.\n\nWhat You Know :\n\n- 5 - 9 years of experience in ML Engineering, AI Platform Engineering, or Cloud AI Deployment roles.\n\n- Strong proficiency in Python, with experience building production-ready AI/ML services and workflows.\n\n- Proven experience deploying and supporting GenAI applications in real-world enterprise environments.\n\n- Experience with orchestration frameworks, including but not limited to Lang Chain, Lang Graph, and Lang Smith.\n\n- Strong knowledge of model serving inference pipelines, monitoring, and observability for AI systems.\n\n- Experience working with cloud AI ecosystems (Azure AI, Azure ML, Databricks preferred).\n\n- Familiarity with containerization and deployment tools (Docker, Kubernetes, REST) and Role & responsibilities.\nSkills\nPython, LangChain, Azure, Databricks, RESTful, Machine Learning, Generative AI, Workflows, Agentic AI","description_format":"text","description_chars":1978,"description_truncated":false,"requirements":{"experience_years_min":5,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams"],"lifecycle":[{"event":"open","at":"2026-09-25T18:04:06Z"}],"liveness":{"score":60,"band":"ok","label":"Likely open","p_open":0.85,"p_active":0.779,"p_room":0.9,"age_days":15,"expected_fill_days":24,"reasons":["seen:15","urgency","velocity","win:mid"],"computed_at":"2026-10-01T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/nisum-platform-engineer","json_url":"https://alion.io/job/nisum-platform-engineer.json","meta":{"generated_at":"2026-10-01T09:13:36Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":34,"day_limit":5000,"remaining_today":4966,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}