Artificial Intelligence & Engineering
AI & Engineering leverages cutting-edge engineering capabilities to help build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These insights are powered by engineering for business advantage, helping transform mission-critical operations.
Join our AI & Engineering team to help transform technology platforms, driving innovation, and help make a significant impact on our clients' achievements. You’ll work alongside talented professionals reimagining and re-engineering operations and processes that could be critical to businesses.
Position Summary
Principal AI System Architect- PROJECT - Engineering and Product Domain - Manager
A leader in AI and engineering, this role helps shape and deliver complex technology solutions that enable business transformation at scale. As a Principal AI System Architect -PROJECT - Engineering and Product Domain -Manager, you will architect multi-agent, distributed, and AI-powered systems for regulated environments, with a focus on performance, resilience, governance, and production readiness. You will work across engineering, data, cloud, and model lifecycle domains to translate business and regulatory requirements into scalable system designs. This role is suited for an experienced architect who brings deep technical knowledge, hands-on delivery experience, and a strong track record of building enterprise-grade AI and distributed platforms.
Work you'll do
As a Principal AI System Architect -PROJECT - Engineering and Product Domain -Manager on the AI & Engineering team, you will be responsible for…
- Architecting high-throughput distributed systems, including event-driven pipeline design, Kafka topic and partition strategy, consumer topology, dead-letter queue patterns, schema evolution, and ETL architecture.
- Designing enterprise AI and machine learning platforms, including retrieval-augmented generation infrastructure, model evaluation frameworks, drift detection approaches, model versioning, promotion controls, rollback strategies, and fine-tuning workflows.
- Leading the design of multi-agent systems, including agent topology, tool and skill architecture, agent-to-agent communication patterns, memory models, guardrails, and human-in-the-loop escalation frameworks.
- Defining secure and scalable cloud platform architectures across infrastructure as code, network and identity design, application integration, observability, auditability, and cost architecture for AI-enabled systems.
- Modeling complex dependency relationships and decision logic using graph databases and rule engines to support production-grade automation, governance, and downstream integration patterns.
The team
Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models—traditional teams, pools, or pods—are tailored to each client’s needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.
Location: Hyderabad/Bengaluru
Shift Timings: 11 AM to 8 PM or 2 PM to 11 PM
Qualifications
Required:
- 12+ years of experience in engineering, including 4+ years at the principal architect or staff architect level
- Experience delivering machine learning or artificial intelligence systems into production in a regulated industry
- Experience writing production-grade code in Python, Node.js, or Go
- Experience designing and implementing production multi-agent systems, including agent tool design, agent-to-agent communication, agent memory architecture, token optimization, guardrails, and human-in-the-loop escalation patterns
- Experience designing distributed systems on Amazon Web Services, including Kafka or Amazon Managed Streaming for Apache Kafka, Amazon EventBridge, Amazon Simple Queue Service, AWS Glue, Amazon Athena, and infrastructure as code using Terraform or AWS Cloud Development Kit
- Experience designing retrieval-augmented generation architectures, model evaluation frameworks, model versioning and rollback approaches, and graph-based data models using Neo4j and Cypher
- Experience designing data contract frameworks, schema versioning approaches, and rule engine or decision table solutions for production environments
Preferred:
- Experience with orchestration tools such as LangGraph or AgentCore
- Experience with large language model platforms such as AWS Bedrock, OpenAI, Anthropic Claude, or Azure OpenAI
- Experience with vector databases or knowledge platforms such as pgvector, Pinecone, Weaviate, or OpenSearch
- Experience with MLOps and evaluation tools such as MLflow, SageMaker, LangSmith, Promptfoo, or Weights & Biases
- Experience with observability tools such as Datadog, Splunk, Langfuse, OpenTelemetry, or Amazon CloudWatch
- Experience with identity, access, and security platforms such as Azure Active Directory, Okta, or Apigee
- Experience with legacy rule extraction, Mainframe modernization and rearchitecture/rewrites
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