AI Agent Workflow Architect Job at NTT DATA (Bangalore)

AI Agent Workflow Architect

The AI Agent Workflow Architect will design and develop workflows for large lang...

Location

India , Bangalore

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

Strong grasp of NLP and generative AI principles
Familiarity with prompt engineering tools and frameworks (e.g., PromptLayer, LangChain)
Experience working with OpenAI, Claude, or open-source LLMs
Attention to language detail, edge cases, and explainability
Understanding of process flows in industries like insurance, lending, or compliance

Job Responsibility

Design prompt templates for LLMs across classification, Q&A, generation, and reasoning tasks
Develop modular agent workflows with decision branches and fallback logic
Conduct prompt evaluation experiments for accuracy, reliability, and UX
Work closely with domain SMEs to map business processes into agent logic
Monitor and iterate based on user interaction and model performance

GCP AI Platform Architect / Lead AI Platform Engineer

Our client is an innovative technology company specializing in the development o...

Location

Poland , Kraków

Salary:

Not provided

TeamQuest Sp. z o. o.

Expiration Date

Until further notice

Requirements

GCP Expertise (verifiable - ask for production examples): GCP is their primary cloud not secondary experience alongside AWS/Azure. Production deployments across most of: Vertex AI, Cloud Run or GKE, Pub/Sub, BigQuery, Secret Manager, VPC Service Controls, IAM + Workload Identity. Has designed for GCP from scratch, not migrated from another cloud, end-to-end ownership
AI / Backend Engineering: Python is the primary language - production-grade service/API development, not scripting or data science only. Strong track record building distributed systems and integrating LLMs.
Agentic Architecture (must be production, not PoC): Hands-on production experience with at least one: LangGraph, Google ADK, CrewAI, or custom multi-agent orchestration layer. RAG pipelines shipped to production. Google ADK: candidate must be able to explain what it is, when to use it, and how it compares to LangGraph and custom orchestration. AI agent workflows, ReAct prompting, and Function Calling in production environments
Multi-Tenant Architecture: Has designed a multi-tenant SaaS platform end-to-end - not just contributed. Can articulate tenant isolation strategies: IAM boundary design, data isolation per tenant, VPC controls.
API Design & Integrations: Proven ability to create secure, high-performance APIs capable of asynchronously managing traffic and communication between multiple decoupled services.
Enterprise Security: Practical knowledge of data isolation in multi-tenant SaaS architectures, IAM, and securing cloud-based environments.
Vector Databases: Hands-on experience with semantic search and at least one of: Pinecone, Weaviate, pgvector, or Vertex Matching Engine.

Job Responsibility

System Architecture: Design and develop a scalable, cloud-native architecture on Google Cloud Platform (GCP) that meets enterprise security and multi-tenant data isolation requirements for a SaaS environment
AI Agent Orchestration: Architect and implement autonomous, multi-step AI workflows with a clear separation of agent responsibilities (retrieval, analysis, reasoning, response generation)
Hands-on Core Development: Actively contribute to core system development-coding orchestration logic, designing services, optimizing performance, and building secure API integrations for routing queries across internal and external agents
Frontend Enablement: Design the backend layer, streaming protocols, and APIs to seamlessly support and integrate with advanced conversational UIs
Data Management & Extensibility: Build a robust backend capable of processing qualitative and social data, ensuring the platform is easily extensible to incorporate new data sources

What we offer

Attractive salary
Full remote work
Social benefits:sporto card,healthcare insurance

Fulltime

GCP AI Platform Architect / Lead AI Platform Engineer

Our client is an innovative technology company specializing in the development o...

Location

Poland , Katowice

Salary:

Not provided

TeamQuest Sp. z o. o.

Expiration Date

Until further notice

Requirements

GCP Expertise (verifiable - ask for production examples): production deployments across most of: Vertex AI, Cloud Run or GKE, Pub/Sub, BigQuery, Secret Manager, VPC Service Controls, IAM + Workload Identity
Has designed for GCP from scratch, not migrated from another cloud, end-to-end ownership
AI / Backend Engineering: Python is the primary language - production-grade service/API development, not scripting or data science only
Strong track record building distributed systems and integrating LLMs
Agentic Architecture (must be production, not PoC): Hands-on production experience with at least one: LangGraph, Google ADK, CrewAI, or custom multi-agent orchestration layer
RAG pipelines shipped to production
Google ADK: candidate must be able to explain what it is, when to use it, and how it compares to LangGraph and custom orchestration
AI agent workflows, ReAct prompting, and Function Calling in production environments
Multi-Tenant Architecture: Has designed a multi-tenant SaaS platform end-to-end - not just contributed
Can articulate tenant isolation strategies: IAM boundary design, data isolation per tenant, VPC controls

Job Responsibility

System Architecture: Design and develop a scalable, cloud-native architecture on Google Cloud Platform (GCP) that meets enterprise security and multi-tenant data isolation requirements for a SaaS environment
AI Agent Orchestration: Architect and implement autonomous, multi-step AI workflows with a clear separation of agent responsibilities (retrieval, analysis, reasoning, response generation)
Hands-on Core Development: Actively contribute to core system development-coding orchestration logic, designing services, optimizing performance, and building secure API integrations for routing queries across internal and external agents
Frontend Enablement: Design the backend layer, streaming protocols, and APIs to seamlessly support and integrate with advanced conversational UIs
Data Management & Extensibility: Build a robust backend capable of processing qualitative and social data, ensuring the platform is easily extensible to incorporate new data sources

What we offer

Attractive salary
Full remote work
Social benefits: sport card, healthcare insurance

Fulltime

AI Tech Lead / AI Architect

The AI Tech Lead / Architect will design and implement enterprise-grade AI solut...

Location

India , Bangalore

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

7+ years software engineering/architecture experience
2+ years delivering AI/GenAI/ Agentic AI solutions in production
Strong architecture skills: distributed services, APIs, integration, security, and reliability
Hands-on experience with RAG and agentic/workflow orchestration patterns
Strong understanding of multi-agent systems, agent orchestration, and coordination patterns
Experience working with LLMs or AI reasoning systems, including managing model limitations and risks
Solid background in enterprise software engineering, APIs, and system integration
Strong understanding of Agentic AI Cognitive Frameworks
Strong understanding of Architectural Components of Agentic AI systems
Python, production-grade engineering practices

Job Responsibility

Multi-agent architecture & workflow orchestration: Define how agents work together (roles, shared context, coordination) and design orchestrated agent workflows for real business processes
Reusable patterns (avoid one-offs): Establish standard reference patterns and starter implementations so teams don’t build bespoke, hard-to-maintain AI solutions
Governance & compliance built-in: Embed practical controls (human-in-the-loop, approvals where needed) and ensure privacy/security expectations are met for sensitive/client data
Observability & production readiness: Ensure solutions have monitoring/telemetry and meet production standards for reliability and operational support
Enterprise integration & access control: Integrate agents with enterprise platforms/data sources and enforce entitlements/least-privilege access to prevent unintended exposure
Technical leadership & translation: Guide engineering teams, act as SME, and translate business objectives into scalable AI architecture that delivers measurable outcomes

AI Tech Lead / AI Architect

The AI Tech Lead / AI Architect will be responsible for designing and scaling en...

Location

India , Bangalore

Salary:

Not provided

NTT DATA

Expiration Date

Until further notice

Requirements

7+ years software engineering/architecture experience
2+ years delivering AI/GenAI/ Agentic AI solutions in production
Strong architecture skills: distributed services, APIs, integration, security, and reliability
Hands-on experience with RAG and agentic/workflow orchestration patterns
Strong understanding of multi-agent systems, agent orchestration, and coordination patterns
Experience working with LLMs or AI reasoning systems, including managing model limitations and risks
Solid background in enterprise software engineering, APIs, and system integration
Strong understanding of Agentic AI Cognitive Frameworks
Strong understanding of Architectural Components of Agentic AI systems
Python, production-grade engineering practices

Job Responsibility

Multi-agent architecture & workflow orchestration: Define how agents work together (roles, shared context, coordination) and design orchestrated agent workflows for real business processes
Reusable patterns (avoid one-offs): Establish standard reference patterns and starter implementations so teams don’t build bespoke, hard-to-maintain AI solutions
Governance & compliance built-in: Embed practical controls (human-in-the-loop, approvals where needed) and ensure privacy/security expectations are met for sensitive/client data
Observability & production readiness: Ensure solutions have monitoring/telemetry and meet production standards for reliability and operational support
Enterprise integration & access control: Integrate agents with enterprise platforms/data sources and enforce entitlements/least-privilege access to prevent unintended exposure
Technical leadership & translation: Guide engineering teams, act as SME, and translate business objectives into scalable AI architecture that delivers measurable outcomes

Fulltime

Ai Architect

We are looking for an experienced AI Architect to shape and deliver enterprise A...

Location

United States , Coppell

Salary:

Not provided

Robert Half

Expiration Date

Until further notice

Requirements

2+ years of experience in architecture, AI solution design, or enterprise technology leadership roles
Demonstrated knowledge of enterprise architecture principles, API development, and microservices design
Hands-on experience with leading AI platforms and tools such as OpenAI, Gemini, GitHub Copilot, and LangChain
Practical understanding of retrieval-augmented generation, prompt design, and modern knowledge-based AI solution patterns
Ability to design secure, scalable, and production-ready AI systems that integrate with business applications and data platforms
Experience collaborating with technical and business stakeholders to translate operational needs into effective technology solutions
Strong communication and leadership skills with the ability to influence direction across cross-functional teams

Job Responsibility

Develop enterprise-wide AI architecture standards, reference models, and implementation guidelines to support consistent solution delivery across business functions
Design and deploy scalable platforms for generative AI, agent-based systems, machine learning, and analytics that can operate effectively in a global environment
Establish governance practices covering model oversight, responsible AI usage, security controls, compliance expectations, and lifecycle management
Partner with senior stakeholders to identify high-impact opportunities where AI can improve operational performance, decision-making, and business outcomes
Lead the architecture and rollout of AI-enabled assistants, knowledge tools, and automated workflows integrated with core enterprise applications and internal data sources
Create robust API, microservices, and orchestration patterns that enable reliable integration of AI services with business platforms and custom solutions
Build and refine retrieval-augmented generation solutions, vector-based search capabilities, prompt frameworks, and enterprise knowledge access models
Work with data engineering and platform teams to implement scalable AI pipelines, MLOps and LLMOps practices, monitoring, and cloud-based deployment patterns across major cloud environments
Evaluate emerging vendors, tools, and proof-of-concept solutions while guiding technical teams through architecture decisions, implementation challenges, and best practices

Fulltime

AI Agent Developer

We’re looking for a Senior AI Engineer to design and build production-grade AI a...

Location

Netherlands , Utrecht

Salary:

Not provided

Levy Professionals

Expiration Date

Until further notice

Requirements

7-10+ years in software engineering with strong Python expertise
Proven experience building agent-based or autonomous systems in production
Strong experience with LLM APIs (e.g. OpenAI), including function calling and orchestration
Hands-on experience with LangChain, LangGraph, AutoGen, or CrewAI
Deep understanding of RAG architectures, vector databases (Pinecone, Weaviate, Azure AI Search), and retrieval optimisation
Strong knowledge of LLM evaluation, prompt optimisation, and safety techniques
Experience with Docker, Kubernetes, and cloud platforms (Azure preferred)
Familiarity with FastAPI and microservices architecture

Job Responsibility

Design and build production-grade AI agents with planning, reasoning, and tool-use capabilities
Architect stateful agent workflows using frameworks like LangGraph or AutoGen
Build and productionise RAG pipelines (data ingestion, embeddings, retrieval optimisation, re-ranking)
Integrate LLMs with enterprise systems via APIs, tools, and external data sources
Establish evaluation, observability, and guardrails (accuracy, safety, latency, cost)
Deploy and operate AI applications using Docker, Kubernetes, and Azure
Drive technical design decisions, mentor engineers, and define best practices for agentic AI development

Fulltime

Software Architect - Ai Platform

We are building an agentic mesh network for US healthcare, deploying multimodal ...

Location

United States , New York City

Salary:

Not provided

Armory Medical

Expiration Date

Until further notice

Requirements

5+ years building production distributed systems
You have designed, shipped, and operated infrastructure that runs at institutional scale
You've made architectural bets that held up — and learned from the ones that didn't

Job Responsibility

Define the architecture of the systems that power autonomous agent orchestration across the most critical vertical within our country
Own entire subsystems — from protocol design to production deployment — with the autonomy and accountability of a technical co-founder
Agent runtime architecture — designing the execution engine, task scheduling, state management, exception handling, and human-escalation pathways that the entire platform runs on
Multi-agent orchestration layer — the coordination primitives, tool-use frameworks, and real-time decision-making pipelines that process clinical documents, voice interactions, and multimodal healthcare data at institutional scale
Federated interoperability protocols that enforce data residency while enabling cross-entity agent collaboration
Platform abstractions — APIs, SDKs, and workflow primitives that allow both internal and external teams to deploy agents on the platform

What we offer

Top-of-market cash compensation plus significant founding-team equity

Fulltime

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AI Agent Workflow Architect

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