Technical Manager

1 week ago

Haryana, India Qode Full time ₹ 15,000 - ₹ 28,00,000 per year
Role Description   We are seeking a skilled Technical Lead to Lead the end-to-end design and delivery of an AI-powered solution —combining NLP, anomaly detection, GenAI/RAG, and rule engines on Cloud platform. Own architecture, technical roadmap, and production reliability while guiding a cross-functional team (ML, Data Eng, Backend, DevOps, QA). Key responsibilities ·      Define reference architecture (ingestion → lakehouse → features/vectors → models → APIs/UX); make build/buy decisions. ·      Select, train, and operationalize NLP, anomaly/fraud models, and GenAI/RAG components; establish human-in-the-loop. ·      Implement experiment tracking, model registry, CI/CD for models, automated evaluation, drift monitoring, rollback. ·      Design retrieval pipelines (chunking, embeddings, vector namespaces), guardrails (prompt policies, allow-lists, PII redaction), and citation-based responses. ·      Oversee feature store, labelling strategy, and high-quality gold datasets; enforce DQ rules and lineage. ·      Right-size SKUs; caching/batching; cost/per-token dashboards; SLOs for latency/throughput. ·      Break down epics/stories, estimate and sequence work, unblock the team, run technical design reviews. ·      Translate business policy into rule + ML ensembles, present options, risks, and trade-offs. ·      Establish testing pyramid (unit, data, model evals, e2e), performance targets, observability dashboards. ·      Produce design docs, runbooks, SOPs; mentor engineers; uplift coding and review standards.
Skills requirements · years of software development experience, with at least 5 years leading AI/ML projects. ·      Supervised/unsupervised modelling, anomaly detection, NLP (extraction, classification, NER), OCR pipelines; evaluation design (precision/recall, ROC/PR). ·      LangChain/LangGraph; embeddings; vector databases / Azure Cognitive Search (vector); prompt engineering & safety patterns. ·      MLflow, model registry, online/offline evals, data/version management; CI/CD for models. ·      Delta Lake/Lakehouse (bronze/silver/gold), Azure Data Lake Gen2, Databricks/ADF, schema/versioning, Great Expectations/Deequ. ·      Python (FastAPI), eventing (Event Grid/Service Bus), containerization (AKS/Azure Container Apps), APIM. ·      Cognitive Search, Azure OpenAI, Key Vault, Monitor/App Insights, Purview, Cosmos DB/Azure SQL. ·      Technical decision-making, cross-team coordination, stakeholder communication, mentoring.   Preferred skills  ·      Certifications in AI/ML disciplines. ·      Hands-on experience with explainable AI and AI governance. ·      Familiarity with regulatory compliance standards for financial data (e.g., SOX, GDPR).   Qualifications ·     Bachelor's Degree in Computer Science or related science field or equivalent. 

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