Computer Systems Analyst

Tata Consultancy Services Ltd

  • New York, NY
  • 30+ days ago
  • $180,000–$230,000 Per Year

Highlights

Implement guardrails: input/output filtering, prompt templates, tool whitelisting, rate limits, and secrets management; perform threat modeling and red teaming. Lead architecture for GenAI/LLM solutions using patterns such as RAG, tool/function calling, and agentic workflows.

Numbers & Facts

LocationNew York, NY
Salary$180,000–$230,000 Per Year

Description

Job Duty Descriptions

  • Lead architecture for GenAI/LLM solutions using patterns such as RAG, tool/function calling, and agentic workflows.
  • Design secure enterprise knowledge integration and define data access/segregation controls.
  • Establish Responsible AI, privacy, and security controls for GenAI.
  • Provide technical leadership across stakeholders; document architecture decisions, risks, and roadmaps; guide teams on performance and cost optimization.
  • Define AI/ML target architecture and reference patterns aligned to business strategy, enterprise standards, and regulatory requirements.
  • Translate business use cases into end-to-end solution designs across data, ML, application, integration, and infrastructure layers.
  • Establish technical guardrails (security, privacy, scalability, performance, observability) for AI/ML platforms and workloads.
  • Review and approve architecture/designs; document decisions, trade-offs, and standards; mentor teams on best practices.
  • Design and govern the AI/ML platform and MLOps lifecycle (data ingestion, training, validation, deployment, monitoring, retraining).
  • Define CI/CD standards for ML (model versioning, reproducible pipelines, automated testing, approvals, rollback).

Day-to-day Tasks

  • Prototype RAG/agent workflows; tune chunking/retrieval.
  • Implement guardrails: input/output filtering, prompt templates, tool whitelisting, rate limits, and secrets management; perform threat modeling and red teaming.
  • • Run architecture workshops with engineering teams to capture requirements and constraints.
  • Create solution blueprints, component diagrams, and integration flows; define non-functional requirements (NFRs).
  • Conduct design reviews, security reviews, and performance reviews; provide actionable remediation guidance.
  • Maintain architecture repository and reusable templates.
  • Define pipeline templates and guardrails; onboard teams to standard training/deployment workflows.
  • Set up model registries, feature stores, and experiment tracking standards; enforce naming/versioning conventions.
  • Implement model monitoring.
  • Create runbooks and release checklists; support go-lives and post-release validation.
  • Perform periodic platform health and cost reviews; recommend tuning and right-sizing actions.

Technology and/or Software used for Duty

  • Azure OpenAI / Vertex AI / Bedrock
  • LangChain / LlamaIndex
  • Vector DB
  • C ontent safety/guardrails (Azure AI Content Safety, policy filters)
  • Python, APIs, Git/Azure DevOps, Docker/Kubernetes
  • Azure/AWS/GCP
  • Kubernetes
  • MLflow
  • Kubeflow / Airflow
  • Git / Azure DevOps
  • Docker / Kubernetes
  • Prometheus / Grafana

Education

Bachelor's degree

Salary Range: $180000 - $230000 a year

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