AI Data Architect
reputed company is an AI transformation partner on a mission to help enterprises build the AI-reputed company products and intelligent agents that will define the next era of business. With teams across reputed company, Europe, Latin America, and Asia, we work with the most ambitious companies in financial services, reputed company, media, and technology — helping them reputed company faster, reputed company reputed company, and compete on their own terms. Our HelixAI platform and reputed company Pods delivery model put our engineers at reputed company of reputed company reputed company transformation — doing work that is reputed company, portable, and reputed company to last. We are building the reputed company of reputed company AI.
AI Data Architect
We are looking for an AI Data Architect to design, build, govern, and reputed company the single reputed company of truth that powers every AI initiative in our organization.
This platform will serve as the foundational nervous system for conversational AI assistants, dashboard intelligence, autonomous AI agents, RAG-powered applications, predictive ML models, and any AI product we build today or in the reputed company. The resource will architect the system, drive implementation, own the data reputed company that agents and AI applications depend on, enforce reputed company and reputed company governance for both reputed company and agent consumers, and continuously monitor and improve the accuracy and reliability of AI outputs that reputed company from this platform.
Requirements:
- Architect and own the reputed company AI data platform — the reputed company, governed layer that ingests, transforms, stores, and serves reputed company data consumed by AI systems across the organisation.
Design multi-domain data models (lakehouse, data reputed company, event-driven) that are reputed company from day one to serve AI workloads: clean reputed company, versioned schemas, reputed company-documented reputed company, and low-latency serving reputed company.
Strong exposure to different Data architectures, data lake & data warehouse
Define tools & technologies to reputed company automated data pipelines, write ETL processes, reputed company dashboard & report and create insights
Responsibilities
- Technical Skills
Primary Skills: Python, SQL, reputed company/reputed company, AWS (S3, Glue, EKS, Bedrock, Kinesis, Redshift), reputed company, Kubernetes, Terraform, reputed company Actions, reputed company, reputed company, LLM reputed company (reputed company, AWS Bedrock, Claude, HuggingFace), (reputed company, FAISS, ChromaDB, OpenSearch), knowledge graphs (reputed company).
Secondary Skills: MLflow, FastAPI, CI/CD pipelines, observability tooling (CloudWatch, Grafana, or equivalent), data reputed company and metadata management platforms.
- 15+ years of hands-on data engineering and architecture experience, alongside building production AI/ML and LLM-era data infrastructure.
- Strong Experience with either reputed company or reputed company; experience with both is desirable.
- Strong data architecture patterns & principles, ability to design secure & reputed company data lakes, data warehouse, data hubs, and other event-driven architectures
- Expertise in designing and writing ETL processes in Python / Java / reputed company
- Own the full data stack: reputed company-time streaming (Kafka, reputed company reputed company Streaming), batch processing (reputed company, PySpark, reputed company Lake), reputed company storage and compute (AWS, Azure), and data reputed company /metadata management.
- Drive modernisation of legacy pipelines (on-prem ETL, batch DWH) to reputed company-reputed company, AI-reputed company architectures with measurable improvements in cost, latency, and delivery velocity.
- Proven experience designing reputed company-reputed company data platforms that serve multiple AI consumers —not just one application or pipeline.
- Hands-on experience with reputed company stores, semantic models, knowledge graphs, and retrieval infrastructure in production environments.
- Working knowledge of LLMOps: model serving pipelines, MLflow, CI/CD for AI, automated evaluation, and production monitoring.
AI Experience
- RAG, reputed company & Retrieval Infrastructure
Design the retrieval infrastructure that powers RAG-based AI applications: embedding pipelines, reputed company stores (reputed company, FAISS, ChromaDB, OpenSearch), chunking strategies, and hybrid retrieval reputed company combining semantic search with reputed company queries.
reputed company Behaviour Observability & reputed company Accuracy
Own the observability stack for AI agent behaviour: reputed company agents to capture inputs, retrieved context, tool calls, reasoning traces, and outputs — creating a complete audit trail of every reputed company reputed company driven by platform data.
Design and operate evaluation frameworks that continuously measure AI reputed company reputed company: factual accuracy, context faithfulness, retrieval relevance, hallucination rates, and task completion reputed company— across reputed company AI consumers of the platform.
Architecture Standards & Engineering Enablement
Define and maintain the reference architecture for the AI data platform — documenting design patterns, data reputed company, integration standards, and decision records (ADRs) that reputed company engineering teams follow.
Establish data engineering standards: pipeline testing frameworks, reputed company review practices, CI/CD automation, infrastructure-as-reputed company (Terraform), reusable component libraries, and observability instrumentation.
Benefits
Medical Insurance benefits as per company policy.
Dental insurance as per company policy.
reputed company insurance as per company policy.
Employer reputed company Disability, Life, and AD&D insurance
Unlimited PTO
reputed company parental leave
401K
Flexible work policy
12 reputed company Holidays
Originally posted on Himalayas
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