{"id":3204468,"url":"https://alion.io/job/delta-air-lines-senior-mlops-engineer","title":"Senior MLOps Engineer","company":{"id":6522,"name":"Delta Air Lines","domain":"delta.com","url":"https://alion.io/company/delta-air-lines","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","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":["Bengaluru, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":23000,"max_usd":48000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":38},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"Blue-Green Deployment","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"LLM","optional":false},{"name":"LLMOps","optional":false},{"name":"NLP","optional":false},{"name":"OpenAI","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"SLI/SLO/SLA","optional":false},{"name":"SQL","optional":false},{"name":"Spark","optional":true}],"status":"live","first_seen_at":"2026-10-24T11:36:30Z","employer_posted_date":null,"last_verified_at":"2026-10-24T11:36:30Z","board_verified":false,"closed_at":null,"days_open":1,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":1},"description":"Design, build, and productionize AI solutions, especially LLM and generative AI workloads, on top of our Enterprise data Platform (Databricks, Azure, OpenAI, and AWS). This role has an emphasis on the operationalization of AI solutions, ensuring AI products are reliable, scalable, secure, and cost-effective in production. You will partner with data engineering, data science, and product teams to turn ideas into robust, continuously running services. \n\nResponsibilities: \nDesign and develop end-to-end AI solutions (from data preparation and feature/embedding engineering through to serving) on the EDP.\nProductionize AI and LLM applications: harden prototypes into resilient, observable services with clear SLAs, SLOs, and runbooks.\nImplement, optimize, and operate data / feature / embedding pipelines that support AI products, working closely with data engineers and data scientists.\nBuild and maintain APIs, batch jobs, and workflows that expose AI capabilities safely to internal users and customer-facing applications.\nEstablish and own observability for AI systems (logging, metrics, tracing, data/quality monitoring, safety, and cost monitoring).\nContribute to and improve MLOps/LLMOps practices: deployment pipelines, versioning, canary/blue-green rollouts, and rollback strategies.\nEnsure security, governance, and responsible AI practices are built into production solutions (access control, PII handling, evaluation, policy enforcement).\nCollaborate with product owners to refine requirements, shape delivery plans, and communicate risks and tradeoffs.\nMentor and support less experienced engineers, contributing to standards, patterns, and best practices for AI engineering on the EDP.\n\nRequirements: \n4-7+ years in software, data, or ML engineering, with at least 2+ years focused on ML or LLM based solutions.\n2+ years experience with Databricks.\nStrong SQL skills.\nStrong Python skills for data and AI (e. g., pandas, PySpark, LLM/AI frameworks, API development).\nHands-on experience with modern data/AI platforms similar to our EDP (e. g., lakehouse, cloud-native data, and ML stacks).\nProven experience building LLM applications (chat/completions, embeddings, RAG, function/tool calling) and integrating them into production systems.\nSolid understanding of data modeling, data quality, and performance considerations for AI workloads (latency, throughput, cost).\nExperience with MLOps / LLMOps tooling and practices (e. g., model registries, experiment tracking, evaluation frameworks, CI/CD).\nStrong grasp of software engineering fundamentals: Git, code review, testing strategies (unit/integration), and documentation.\nExperience working closely with data engineers, data scientists, and product teams to deliver production solutions.\n\nBehavioral Competencies: \nAbility to produce high-quality results, work in a collaborative environment by embracing diverse perspectives and use a solution-based approach.\nAdapts communication clearly and concisely based on team dynamics and expresses thoughts and ideas effectively.\nAbility to engage effectively with peers and stakeholders to build trust and reliable working relationships.\nAbility to understand business processes, implement innovative solutions, and guide juniors on continuous improvement by constantly updating oneself on current technology and trends.\nInquisitive to understand customer and business expectations while creating value added on technical solutions.\n\nPreferred Qualification: \nExperience with OpenAI, Azure, and/or AWS within an enterprise data platform context.\nKnowledge of prompt engineering techniques and evaluation methods to improve reliability and reduce hallucinations.\nBackground in statistics, NLP, information retrieval, or related fields.\nSkills\ndatabricks, llmops, mlops, python, sql","description_format":"text","description_chars":3794,"description_truncated":false,"requirements":{"experience_years_min":4,"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":["Air Transport","Commercial Aviation"],"lifecycle":[{"event":"open","at":"2026-10-24T11:36:30Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":0,"expected_fill_days":27,"reasons":["seen:0","velocity","win:early"],"computed_at":"2026-10-25T05:49:26Z"},"pay":null,"html_url":"https://alion.io/job/delta-air-lines-senior-mlops-engineer","json_url":"https://alion.io/job/delta-air-lines-senior-mlops-engineer.json","meta":{"generated_at":"2026-10-25T21:50:10Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per 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