Zensar Technologies
Website:
zensar.com
Job details:
Job Description
Job Title
Senior GenAI Data Engineering Developer (AI/GenAI Architect – Hands-on)
Experience
8–12 years (Data/AI Engineering), with
2+ years in
AI/GenAI architecture and solution design
Role Summary
We’re seeking a
hands-on GenAI Data Engineering leader who can architect and build
production-grade GenAI solutions—from
data pipelines and vectorization to
RAG,
LLM orchestration,
governance, and
cost-aware operations. You will translate business problems into
secure, scalable, and compliant AI systems using
LLMs,
embeddings, and
modern data stacks across
Azure/AWS/GCP.
Key ResponsibilitiesArchitecture & Solutioning
- Lead end-to-end GenAI solution architecture (Assess → Design → Build → Operate) for use cases like RAG/Q&A, copilots, summarization, classification, agents, autonomous workflows.
- Define LLMOps/MLOps blueprints: environments, CI/CD, model registry, observability, evaluation, A/B testing, canary rollouts, guardrails.
- Design RAG architectures: document loaders, chunking strategies, embeddings selection, vector schema design, re-ranking, caching, and fallbacks.
- Establish data governance for AI: PII handling, safety, red-teaming, content filters, model risk, usage policies, and auditability.
Data & Platform Engineering
- Build robust ingestion & transformation pipelines (batch/streaming) to prepare high-quality corpora for LLMs.
- Operationalize chunking/embedding/vector indexing, metadata enrichment, synonyms/ontologies, and semantic retrieval performance tuning.
- Implement feature/knowledge stores, vector DBs, and document stores (e.g., Azure AI Search, Elasticsearch, Pinecone, Weaviate, Milvus, pgvector).
- Integrate orchestration frameworks (Airflow/Prefect/AKS/Databricks Jobs) and API gateways.
Application & Orchestration
- Develop prompt pipelines (system/hybrid prompts, tool-use), retrieval chains, agents, function-calling, and tool integrations (SQL, search, APIs).
- Build and harden LLM applications (e.g., FastAPI/Flask/Functions) with authentication/authorization, rate-limiting, telemetry, and cost controls.
- Introduce guardrails (PII scrubbing, jailbreak mitigation, toxicity, hallucination checks) and evaluation harnesses (BLEU/ROUGE/METEOR, custom rubric scoring, human-in-the-loop).
Ops, Observability & Cost
- Set up model and app observability (latency, token usage, failure modes, retrieval quality, drift detection).
- Implement cost monitoring (per-call, per-user, per-use-case), prompt/embedding caching, and routing to optimize spend/performance.
- Drive SLA/SLO definitions, incident runbooks, and reliability engineering practices.
Stakeholder Leadership
- Partner with Product, Security, Compliance, and Enterprise Architecture to align business outcomes with responsible AI.
- Lead technical design reviews, mentor developers, and contribute to standards/patterns across teams.
Must-Have Skills
- GenAI Architecture & Delivery
- Proven design/delivery of RAG and LLM apps in production
- Expertise in prompt engineering, prompt templating, evaluation, guardrails
- Experience with model selection (proprietary vs open-source), routing, and fallback strategies
- Data Engineering Excellence
- Strong in Python (data processing, APIs, ETL/ELT, testing)
- Proficient with SQL (analytical queries, performance tuning, stored procedures as needed)
- Experience building scalable pipelines (Databricks/Spark, Airflow/Prefect, Kafka/EventHub)
- Vector & Retrieval Systems
- Hands-on with vector databases and embedding pipelines
- Mastery of chunking, retrieval optimization, re-ranking, metadata strategies
- Cloud & Platform
- One or more: Azure (OpenAI, AI Search, Databricks, ADF/ADF v2/Synapse, AKS/Functions), AWS (Bedrock, OpenSearch, Sagemaker, Lambda/EKS), GCP (Vertex AI, BigQuery, GKE)
- Containerization & CI/CD: Docker, Kubernetes, GitHub Actions/Azure DevOps/Jenkins
- Security, Governance & Compliance
- Experience implementing Responsible AI, data privacy/PII, RBAC/ABAC, secret management, network isolation, policy-as-code
- Communication & Leadership
- Ability to translate business problems to GenAI architectures and guide teams through delivery
Nice-to-Have Skills
- LLM Frameworks & Tools: LangChain, LlamaIndex, Semantic Kernel, DSPy
- Observability/Eval: MLflow, Promptfoo, TruLens, Arize, EvidentlyAI, OpenTelemetry, Kibana/Grafana
- Search/Retrieval: Elasticsearch/OpenSearch, Redis Stack, Vespa
- NLP/ML: Transformers, fine-tuning/LoRA, vector quantization, distillation
- Data Quality: Great Expectations/Deequ, Monte Carlo
- Edge/Hybrid: On-prem GPU, NVIDIA NIM, Triton Inference Server
- Compliance: SOC2, HIPAA, GDPR familiarity in AI contexts
Qualifications
- Bachelor’s/Master’s in Computer Science, Data Engineering, AI/ML, or related field
- 8–12 years in data/AI engineering; 2+ years in GenAI/LLM architecture
- Track record delivering secure, reliable, cost-efficient GenAI solutions at enterprise scale
Responsibilities
Senior GenAI Data Engineering Developer (AI/GenAI Architect – Hands-on)
Qualifications
Senior GenAI Data Engineering Developer (AI/GenAI Architect – Hands-on)
About Us
At Zensar, we’re
“experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose:
Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is
ONE with Client - a set of four core values that reflect who we are and how we work:
One Zensar, Nurturing, Empowering, and Client Focus.
Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.
We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.
Click on Apply to know more.