AI & Data Engineering Architect
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Before you apply
LocationHyderabad, India
Work modehybrid
Typefull-time
SeniorityLead
DepartmentSoftware Engineering
Company size10,000+ people
First seenOct 18, 2026 · 3w ago
Verified live19h ago
At a glanceSummarised by Seekless from the posting.
Lead the architecture, design, and implementation of enterprise-scale Agentic AI platforms and intelligent automation solutions
Define and drive the organization's AI/ML architecture strategy, reference architectures, standards, and best practices
Design and implement advanced multi-agent systems using frameworks such as LangGraph, AutoGen, LlamaIndex
Architect complex Retrieval-Augmented Generation (RAG) solutions leveraging vector databases, knowledge graphs, semantic search, and enterprise data platforms
Develop scalable agentic workflows incorporating tool-calling, memory management, planning, reasoning, reflection, and human-in-the-loop capabilities
Lead the integration of LLM-powered applications utilizing Azure OpenAI, AWS Bedrock, and other enterprise AI services while ensuring performance, security, and cost optimization
Design enterprise-grade data architectures utilizing Snowflake, Apache Iceberg, Vector Databases, and cloud-native data platforms to support AI and analytics workloads
Establish standards and frameworks for model lifecycle management, experimentation, deployment, monitoring, observability, and governance using MLflow and modern MLOps practices
Define and implement enterprise AI security controls, including OAuth authentication, fine-grained authorization, role-based access control, data protection, and model governance frameworks
Drive AI platform modernization initiatives through containerization and orchestration technologies including Docker, Kubernetes, and cloud-native deployment architectures
Establish reusable patterns for Model Context Protocol (MCP) integration, external tool orchestration, AI application interoperability, and agent communication frameworks
Collaborate with business leaders, product owners, and engineering teams to identify AI transformation opportunities and translate business objectives into scalable technical solutions
Lead architectural reviews and provide technical oversight for AI/ML projects across multiple teams and business domains
Develop enterprise standards for RAG evaluation, prompt management, agent testing, model monitoring, AI safety, and responsible AI implementation
Partner with Data Engineering teams to architect robust data ingestion, transformation, and orchestration pipelines using dbt, Airflow, Snowflake, and Apache Iceberg
Drive continuous innovation by evaluating emerging AI technologies, open-source frameworks, foundation models, and industry best practices
Serve as the organization's subject matter expert for Agentic AI, Generative AI, Enterprise AI Architecture, and Intelligent Automation
Mentor and guide senior engineers, data scientists, AI developers, and solution architects on architecture decisions and engineering best practices
Influence technology roadmaps and long-term platform strategy for AI, data, and analytics capabilities
Establish AI Center of Excellence standards, reusable frameworks, and governance processes across the enterprise
Lead proof-of-concepts, architecture assessments, technology evaluations, and vendor engagements
Provide thought leadership on emerging AI trends, autonomous agents, foundation models, AI governance, and enterprise adoption strategies
Deep expertise in Agentic AI architectures, multi-agent collaboration frameworks, and autonomous workflow orchestration
Strong experience building enterprise-grade RAG systems, semantic search solutions, vector databases, and knowledge retrieval platforms
Advanced proficiency in Python, AI orchestration frameworks (LangGraph, AutoGen, LlamaIndex), and cloud AI platforms
Extensive experience with Snowflake, Apache Iceberg, distributed data engineering, and large-scale enterprise data ecosystems
Expertise in MLOps, CI/CD, MLflow, Kubernetes, Docker, and production AI deployment patterns
Strong understanding of AI governance, model security, compliance, privacy, and responsible AI principles
Experience designing highly scalable, resilient, and secure AI platforms capable of supporting enterprise-wide adoption
We are an equal opportunity employer and value diversity at our company
We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status
We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment
Skills
Python
LangGraph
AutoGen
LlamaIndex
Azure OpenAI
AWS Bedrock
Snowflake
Apache Iceberg
Vector Databases
MLflow
Docker
Kubernetes
dbt
Airflow
OAuth
Model Context Protocol (MCP)
Benefits
Health insurance
Life insurance
Pension retirement
Paid time off
Family care leave
Are you ready to make an impact at DTCC?
Do you want to work on innovative projects, collaborate with a dynamic and supportive team, and receive investment in your professional development? At DTCC, we are at the forefront of innovation in the financial markets. We are committed to helping our employees grow and succeed. We believe that you have the skills and drive to make a real impact. We foster a thriving internal community and are committed to creating a workplace that looks like the world that we serve.
Pay and Benefits:
•
Competitive compensation, including base pay and annual incentive
•
Comprehensive health and life insurance and well-being benefits, based on location
•
Pension / Retirement benefits
•
Paid Time Off and Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
•
DTCC offers a flexible/hybrid model of 3 days onsite and 2 days remote (onsite Tuesdays, Wednesdays and a third day unique to each team or employee).
The Impact you will have in this role:
The Development family is responsible for creating, designing, deploying, and supporting applications, programs, and software solutions. May include research, new development, prototyping, modification, reuse, re-engineering, maintenance, or any other activities related to software products used internally or externally on product platforms supported by the firm. The software development process requires in-depth subject matter expertise in existing and emerging development methodologies, tools, and programming languages. Software Developers work closely with business partners and / or external clients in defining requirements and implementing solutions. The Software Engineering role specializes in planning, documenting technical requirements, designing, developing, and testing all software systems and applications for the firm. Works closely with architects, product managers, project management, and end-users in the development and enhancement of existing software systems and applications, proposing and recommending solutions that solve complex business problems.
Responsibilities
Key Responsibilities
•
Lead the architecture, design, and implementation of enterprise-scale Agentic AI platforms and intelligent automation solutions that support critical business functions and data-driven decision making.
•
Define and drive the organization’s AI/ML architecture strategy, reference architectures, standards, and best practices across data, model, infrastructure, and governance layers.
•
Design and implement advanced multi-agent systems using frameworks such as LangGraph, AutoGen, LlamaIndex, and emerging agent orchestration technologies.
•
Architect complex Retrieval-Augmented Generation (RAG) solutions leveraging vector databases, knowledge graphs, semantic search, and enterprise data platforms.
•
Develop scalable agentic workflows incorporating tool-calling, memory management, planning, reasoning, reflection, and human-in-the-loop capabilities.
•
Lead the integration of LLM-powered applications utilizing Azure OpenAI, AWS Bedrock, and other enterprise AI services while ensuring performance, security, and cost optimization.
•
Design enterprise-grade data architectures utilizing Snowflake, Apache Iceberg, Vector Databases, and cloud-native data platforms to support AI and analytics workloads.
•
Establish standards and frameworks for model lifecycle management, experimentation, deployment, monitoring, observability, and governance using MLflow and modern MLOps practices.
•
Define and implement enterprise AI security controls, including OAuth authentication, fine-grained authorization, role-based access control, data protection, and model governance frameworks.
•
Drive AI platform modernization initiatives through containerization and orchestration technologies including Docker, Kubernetes, and cloud-native deployment architectures.
•
Establish reusable patterns for Model Context Protocol (MCP) integration, external tool orchestration, AI application interoperability, and agent communication frameworks.
•
Collaborate with business leaders, product owners, and engineering teams to identify AI transformation opportunities and translate business objectives into scalable technical solutions.
•
Lead architectural reviews and provide technical oversight for AI/ML projects across multiple teams and business domains.
•
Develop enterprise standards for RAG evaluation, prompt management, agent testing, model monitoring, AI safety, and responsible AI implementation.
•
Partner with Data Engineering teams to architect robust data ingestion, transformation, and orchestration pipelines using dbt, Airflow, Snowflake, and Apache Iceberg.
•
Drive continuous innovation by evaluating emerging AI technologies, open-source frameworks, foundation models, and industry best practices.
Leadership & Strategic Responsibilities
•
Serve as the organization’s subject matter expert for Agentic AI, Generative AI, Enterprise AI Architecture, and Intelligent Automation.
•
Mentor and guide senior engineers, data scientists, AI developers, and solution architects on architecture decisions and engineering best practices.
•
Influence technology roadmaps and long-term platform strategy for AI, data, and analytics capabilities.
•
Establish AI Center of Excellence standards, reusable frameworks, and governance processes across the enterprise.
•
Lead proof-of-concepts, architecture assessments, technology evaluations, and vendor engagements.
•
Provide thought leadership on emerging AI trends, autonomous agents, foundation models, AI governance, and enterprise adoption strategies.
Requirements
Technical Expertise Expected
•
Deep expertise in Agentic AI architectures, multi-agent collaboration frameworks, and autonomous workflow orchestration.
•
Strong experience building enterprise-grade RAG systems, semantic search solutions, vector databases, and knowledge retrieval platforms.
•
Advanced proficiency in Python, AI orchestration frameworks (LangGraph, AutoGen, LlamaIndex), and cloud AI platforms.
•
Extensive experience with Snowflake, Apache Iceberg, distributed data engineering, and large-scale enterprise data ecosystems.
•
Expertise in MLOps, CI/CD, MLflow, Kubernetes, Docker, and production AI deployment patterns.
•
Strong understanding of AI governance, model security, compliance, privacy, and responsible AI principles.
•
Experience designing highly scalable, resilient, and secure AI platforms capable of supporting enterprise-wide adoption
Legal
Actual salary is determined based on the role, location, individual experience, skills, and other considerations. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.