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AI Engineering Architect

Infosys
Bengaluru, India
13-15 Years
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Job Description

  • 13+ years of experience in software engineering with 3+ years in AI with strong architecture ownership
  • Proven experience designing and implementing enterprise-scale AI engineering or MLOps platforms
  • Strong hands on experience with LLMs, prompt engineering, RAG, and agent frameworks
  • Proficiency in Python, AI frameworks, and cloud-native AI services
  • Experience in Kubernetes, CI/CD, and secure deployment of AI models
  • Experience integrating AI capabilities into enterprise scale systems Good to Have Skills
  • Experience with multi agent orchestration and autonomous workflows
  • Knowledge of model observability and monitoring tooling
  • Exposure to QE platforms, test automation frameworks, or AI assisted testing
  • Domain experience in regulated industries such as BFSI, Healthcare, Telecom
  • Cloud and AI certifications

AI Architecture & Engineering

  • Define and own AI reference architectures for generative AI, agentic systems, and AI augmented applications
  • Architect scalable solutions using LLMs, multi agent systems, orchestration frameworks, and AI pipelines
  • Design AI platforms supporting model serving, prompt management, RAG, and workflow orchestration
  • Establish architectural standards for performance, scalability, reliability, and cost efficiency Platform Engineering & Integration
  • Build reusable AI components for LLM integration, vector search, embeddings, and inference services
  • Enable secure and scalable deployment using Kubernetes, serverless platforms, and CI/CD pipelines
  • Integrate AI capabilities into enterprise systems using APIs, SDKs, and event driven architectures
  • Collaborate with QE teams to embed AI into test automation, test data generation, and intelligent validation Engineering Governance & Quality
  • Define architectural guardrails for model lifecycle, versioning, monitoring, and rollback
  • Ensure adherence to non functional requirements including performance, observability, and fault tolerance
  • Leverage observability tools to monitor model performance and drift
  • Review designs and implementations for architectural compliance and code quality
  • Mentor engineers and architects on AI engineering best practices Core Platforms, Frameworks & Tooling
  • LLM and foundation model platforms (e.g., AWS Bedrock, Azure OpenAI, Vertex AI)
  • Agentic AI and orchestration frameworks (LangChain, LangGraph, CrewAI, AutoGen, Google ADK or equivalent)
  • Vector databases and search technologies (OpenSearch, Pinecone, FAISS, Weaviate)
  • Model lifecycle and deployment tooling (Kubernetes, containers, serverless runtimes)
  • CI/CD and MLOps tooling for AI pipelines (GitHub Actions, Azure DevOps, Jenkins)
  • Observability and monitoring tooling for AI systems (OpenTelemetry, Prometheus, Grafana) Client Orientation & Leadership
  • Partner with product and engineering teams to identify AI opportunities and shape roadmaps
  • Support client workshops, RFPs, and solution presentations
  • Mentor engineers on AI/ML/Gen AI best practices and emerging technologies
  • Translate complex AI concepts into business-friendly narratives.

More Info

Job Type:
Permanent Job
Industry:
Other
Employment Type:
Full time

About Company

Infosys

Job ID: 150844435

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Last Updated: 07-07-2026 06:54:40 AM
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