{"id":3363132,"url":"https://alion.io/job/cctech-ai-engineer","title":"AI Engineer","company":{"id":4434432,"name":"CCTech","domain":"cctech.co.in","url":"https://alion.io/company/cctech-2","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Zoho Recruit","truth_index":{"grade":"C","score":63,"open_postings":29,"ghost_share":0.621,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-06T05:58:05Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Ahmedabad, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Function Calling","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Machine Learning","optional":false},{"name":"PEFT","optional":false},{"name":"RAG","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true},{"name":"Docker","optional":true},{"name":"Embeddings","optional":true},{"name":"FAISS","optional":true},{"name":"FastAPI","optional":true},{"name":"GCP","optional":true},{"name":"LangChain","optional":true},{"name":"LangGraph","optional":true},{"name":"MLFlow","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"pgvector","optional":true},{"name":"Pinecone","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true},{"name":"Scikit-learn","optional":true},{"name":"SQL","optional":true},{"name":"TensorFlow","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-09-01T00:00:00Z","employer_posted_date":"2026-09-01","last_verified_at":"2026-11-06T04:05:48Z","board_verified":true,"closed_at":null,"days_open":66,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":66},"description":"The AI Engineer designs, builds, and operationalises machine learning and generative AI systems, taking them from prototype to production. The role covers model development, LLM and agentic application engineering, and the data and deployment pipelines that keep these systems accurate, scalable, and reliable.Key\nResponsibilities:\nBuild, evaluate, and deploy machine learning and deep learning models for production.\nDevelop LLM-based and agentic applications, including RAG pipelines and tool use.\nFine-tune and optimise models for accuracy, latency, and cost using PEFT and quantisation.\nDesign evaluation frameworks, benchmarks, and guardrails to safeguard model quality.\nBuild and automate data pipelines for training, inference, and model monitoring.\nPackage and serve models as scalable APIs with containerisation, CI/CD, and MLOps.\nStay updated with advancements in AI/ML and apply them to practical use cases.\nRequirements Educational\nQualifications:\nB.E./B.Tech, M.Tech, B.Sc., M.Sc., MCA, or an equivalent degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, or a related quantitative field.\nRelevant certifications in cloud, AI/ML, or software engineering are a plus. Skillset:\nStrong programming skills in Python.\nExperience with ML/DL frameworks (e.g., scikit-learn, PyTorch, or TensorFlow).\nHands-on experience with LLM APIs, prompt engineering, and agent frameworks (e.g., LangChain, LangGraph, MCP).\nWorking knowledge of RAG, embeddings, and vector databases (e.g., pgvector, FAISS, or Pinecone).\nExperience serving models as APIs (FastAPI, Docker) with MLOps practices (MLflow, model versioning, monitoring).\nProficiency with SQL and data pipeline tooling for large datasets.\nExperience with at least one cloud platform (AWS, Azure, or GCP).\nSoft Skills:\nAdaptability in a fast-evolving technology landscape.\nStrong problem-solving ability with a structured, hands-on approach.\nCritical thinking to evaluate trade-offs and validate AI generated outputs.\nBenefits Opportunity to work with a dynamic and fast-paced engineering IT organization. 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