Technology Architect

About The Role

Project Role :Technology Architect

Project Role Description :Review and integrate all application requirements, including functional, security, integration, performance, quality and operations requirements. Review and integrate the technical architecture requirements. Provide input into final decisions regarding hardware, network products, system software and security.

Must have skills :Python (Programming Language)

Good to have skills :CommerceTools Commerce Platform
Minimum

5 year(s) of experience is required

Educational Qualification :15 years full time education

Summary:Lead the engineering delivery of GenAI products. Own technical decisions, solution quality, and team execution across front end, back end, and cloud AI services. Mentor developers, standardize patterns, and ensure secure, scalable deployments.

Roles & Responsibilities:

Translate business requirements into solution blueprints (LLM selection, RAG architecture, data contracts, API design).

Own non functional targets (latency, scalability, cost, resilience) and guide performance engineering.

Establish coding standards for Python/TypeScript; enforce test coverage, secure practices, and review discipline.

Design RAG pipelines at scale:ingestion jobs, metadata schema, hybrid search (embeddings), re ranking.

Decide cloud service mix and deployment topology across AWS/Azure/GCP; optimize token/cost with caching, response shaping, batching.

Integrate observability (logs, traces, metrics), evaluation (hallucination/toxicity/bias), and responsible AI controls.

Plan and run CI/CD & MLOps (model/config versioning, feature flags, canary/blue green).

Mentor engineers; unblock delivery; collaborate with architects, product, and security.

Professional & Technical Skills:

Deep hands on Python + system design for microservices/REST/graphql; front end in React/Angular.

Proven LLM & RAG solutioning:retrieval strategies, grounding sources, prompt/tool orchestration, guardrails.

Cloud design patterns:

AWS:Bedrock, Lambda/Step Functions, SageMaker endpoints, Kendra/OpenSearch, CloudWatch.

Azure:OpenAI, Functions/AKS, Cosmos DB, Azure AI Search, Monitor/Log Analytics.

GCP:Vertex AI, Cloud Run, BigQuery, AlloyDB, Vertex Search/RAG.

Security & compliance:OAuth2/OIDC, secret rotation, data residency, PII handling, prompt security.

Performance & cost engineering for LLMs (token budgets, context packing, streaming).

Additional Information:

Bachelors/Masters in CS/Engineering (or equivalent).

Typically 1014 years total experience; 36 years in AI/GenAI.

Demonstrated team leadership across 612 engineers.

Qualification15 years full time education