{"id":1160373,"url":"https://alion.io/job/nagarro-senior-staff-engineer-generative-ai-2","title":"Senior Staff Engineer, Generative AI","company":{"id":2457,"name":"Nagarro","domain":"nagarro.com","url":"https://alion.io/company/nagarro","size_band":"5000+","is_staffing_agency":false,"employer_type":"services","is_intermediary":false,"listed_via":null,"ats_vendor":"SmartRecruiters","truth_index":{"grade":"A","score":94,"open_postings":95,"ghost_share":0,"stale_share":0.232,"repost_share":0,"time_to_fill_p50_days":29,"computed_at":"2026-09-26T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["India"],"countries":["IN"],"hiring_countries":["IN"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":48000,"max_usd":107000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":775},"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Azure","optional":false},{"name":"BERT","optional":false},{"name":"Claude","optional":false},{"name":"Cortex","optional":false},{"name":"FastAPI","optional":false},{"name":"Fine-tuning","optional":false},{"name":"Hugging Face","optional":false},{"name":"Knowledge Distillation","optional":false},{"name":"LangChain","optional":false},{"name":"LangGraph","optional":false},{"name":"LangSmith","optional":false},{"name":"Llama","optional":false},{"name":"LlamaIndex","optional":false},{"name":"Machine Learning","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Model Distillation","optional":false},{"name":"Neo4j","optional":false},{"name":"Pandas","optional":false},{"name":"Perplexity","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Qwen","optional":false},{"name":"RAG","optional":false},{"name":"Scikit-learn","optional":false},{"name":"SciPy","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false},{"name":"Weaviate","optional":false},{"name":"Prometheus","optional":true}],"status":"live","first_seen_at":"2026-09-21T11:05:07Z","employer_posted_date":"2026-09-21","last_verified_at":"2026-09-26T23:53:27Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"We're Nagarro.\nWe are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale - across all devices and digital mediums, and our people exist everywhere in the world (18000+ experts across 40 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in!\n REQUIREMENTS:\nTotal experience 8+ years.\nDeep understanding of LLMs (e.g., GPTs, Llama, Claude, Gemini, Qwen, Mistral, BERT-family models) and their architectures (Transformers)\nShould have expert-level prompt engineering skills and proven experience implementing RAG patterns\nHigh proficiency in Python and standard AI/ML libraries (e.g., LangChain, LlamaIndex, LangGraph, LangSmith, Hugging Face Transformers, Scikit-learn, PyTorch/TensorFlow).\nExperience implementing RAG architectures and prompt engineering.\nStrong experience with fine-tuning and distillation techniques and evaluation.\nMust have experience in Python, SQL, Pandas, SciPy, and Scikit-learn, ML model development, validation, deployment, and tuning\nShould have done anomaly-detection implementation\nMust have experience with Snowflake Data Cloud and Snowflake Cortex AI.\nStrong experience using managed AI/ML services on the target cloud platform (e.g., Azure Machine Learning Studio, AI Foundry).\nStrong understanding of vector databases (e.g., Weaviate, Neo4j)\nShould have understanding of GenAI evaluation metrics (e.g., BLEU, ROUGE, perplexity, semantic similarity, human evaluation).\nArchitect and implement scalable GenAI and Agentic AI solutions end-to-end.\nShould be able to write high-quality, production-ready Python code with strong testing and maintainability practices.\nShould be able to productionize AI systems on Azure or AWS, ensuring enterprise-grade reliability and performance.\nShould be able to build and expose APIs using FastAPI, integrating with databases through an ORM.\nShould be able to scale GenAI solutions to support enterprise workloads.\nCollaborate across product and engineering teams to convert business needs into AI-driven solutions.\nStrong ability to both architect and code GenAI/Agentic AI solutions.\nProven production experience with GenAI deployments on Azure or AWS.\nStrong experience in scaling AI solutions in live environments.\nShould have successfully delivered at least one production GenAI/Agentic AI solution.\nShould have familiarity with Model Context Protocol (MCP).\nShould have contributions to open-source GenAI projects.\nExcellent communication skills and the ability to collaborate effectively with cross-functional teams.\nRESPONSIBILITIES:\nUnderstanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.\nMapping decisions with requirements and be able to translate the same to developers.\nIdentifying different solutions and being able to narrow down the best option that meets the clients’ requirements.\nDefining guidelines and benchmarks for NFR considerations during project implementation.\nWriting and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers.\nReviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.\nDeveloping and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it.\nUnderstanding and relating technology integration scenarios and applying these learnings in projects.\nResolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.\nCarrying out POCs to make sure that suggested design/technologies meet the requirements.\n Bachelor’s or master’s degree in computer science, Information Technology, or a related field.","description_format":"text","description_chars":4120,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[{"language":"English","level":"All levels","optional":false}]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["IT Consulting & Digital Transformation","IT Outsourcing & Dedicated Teams","Custom Software Development","Cloud Consulting & Migration"],"lifecycle":[{"event":"open","at":"2026-09-23T23:32:42Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.896,"p_room":1,"age_days":4,"expected_fill_days":29,"reasons":["conf:3","velocity","win:early","comp:brand"],"computed_at":"2026-09-26T05:45:00Z"},"pay":null,"html_url":"https://alion.io/job/nagarro-senior-staff-engineer-generative-ai-2","json_url":"https://alion.io/job/nagarro-senior-staff-engineer-generative-ai-2.json","meta":{"generated_at":"2026-09-27T05:33:53Z","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":4889,"day_limit":5000,"remaining_today":111,"minute_limit":60,"resets_at":"2026-09-28T00:00:00Z"}}}