AI/ML Architect in Hyderabad, भारत

Job Summary : We are looking for experienced AI/ML Architects to join our AI Engineering service line. In this role, you will anchor the technical delivery of enterprise AI/Agentic AI projects post deal-closure. You will take over from solution architects and lead the design, build, deployment, and optimization of AI/ML systems - ensuring production-grade quality, scalability, and https://jobeax.com/link/F5cIpI8N7K5wqHzx Responsibilities : Architecture & Technical Leadership : - Own the end-to-end technical architecture and solution integrity during project delivery.- Translate solution blueprints into detailed technical designs, backlog, and integration plans.- Lead detailed design reviews, ensure alignment with AI platform, MLOps, and Agentic AI best practices.- Select appropriate frameworks, APIs, libraries, and cloud-native services for https://jobeax.com/link/eGPLX2Cmh2eoaGEY Execution & Delivery Oversight : - Serve as technical anchor for customer AI/ML and Agentic AI projects.- Guide engineering teams on modular, secure, and reusable implementation strategies.- Review and validate code, infrastructure scripts, and ML pipelines for quality, performance, and reliability.- Oversee data pipelines, model training, LLMOps, and model deployment workflows.Hands-on Engineering & Problem Solving : - Provide hands-on support for complex components : LLM pipelines, vector stores, fine-tuning, evaluations.- Resolve system integration challenges across APIs, knowledge stores, and orchestration layers.- Implement or validate MLOps workflows using MLflow, Airflow, Argo, KServe, BentoML, https://jobeax.com/link/KhjAed5QtTkzB8A3, Compliance & Observability : - Embed observability, safety, and compliance into the AI/ML lifecycle.- Integrate with AI governance platforms for model tracking, versioning, audits, and risk controls.- Ensure alignment with enterprise and regulatory standards like NIST AI RMF, EU AI Act, and internal responsible AI https://jobeax.com/link/Ns5a6YPKGFW8hcXe & Customer Engagement : - Act as the technical point of contact for client-side engineering and data science teams during delivery.- Participate in sprint planning, status reviews, and change control boards.- Support knowledge transfer, UAT, documentation, and post-deployment https://jobeax.com/link/KV62UrCi4iDASVmf Qualifications : - Education : https://jobeax.com/link/yZvtq40aJzRI3Eg6 or equivalent in Computer Science, Data Science, or a related field.- Experience : 10+ years in software architecture or engineering with 5+ years in applied AI/ML system delivery.- Strong Python development skills; proficiency in ML/AI frameworks (PyTorch, TensorFlow, Scikit-learn).- Strong understanding of LLMs, RAG pipelines, vector databases (Weaviate, Qdrant, Pinecone).- Experience with MLOps/LLMOps tools : MLflow, Argo, KServe, Feast, Kubeflow.- Proficiency in data pipeline engineering using Spark, Airflow, or DataFlow.- Exposure to agent orchestration frameworks : LangChain, LangGraph, AutoGen, https://jobeax.com/link/ykD3x1hvPWZi0lVs & Infrastructure : - Hands-on experience with GCP (Vertex AI, BigQuery, Document AI, AI Gateway) and/or Azure (Azure ML, OpenAI, Synapse).- Expertise in containerization (Docker) and orchestration (Kubernetes).- Familiarity with Infrastructure as Code (Terraform, Pulumi, CDK).Soft Skills : - Strong architectural thinking and problem-solving in fast-paced delivery environments.- Excellent communication and collaboration skills to work across cross-functional teams and clients.- Proactive, structured, and detail-oriented with a bias for https://jobeax.com/link/yJDaFl6Xs8aZ6SII to Have : - Experience in real-world deployments of Agentic AI systems or collaborative multiagent setups.- Exposure to regulatory/ethical concerns in AI such as fairness, transparency, or bias mitigation.- Familiarity with AI observability, explainability, and governance tooling (e.g., Arize, Fiddler, TruEra). (ref:hirist.tech)