Applied AI Solution Architect
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Job Description
Applied AI architect building production-ready agentic systems for phData, a data and AI consultancy. Designing reusable accelerators and advising enterprise clients across India delivery operations.
Responsibilities:
- Own and drive end-to-end architecture, solution design, and delivery of agentic AI solutions for enterprise clients across diverse industries
- Design and build reusable agentic accelerators and reference architectures aligned with the Intelligence Platform
- Translate ambiguous business problems into clear agentic solution designs
- Architect production-grade agents emphasizing reliability, scalability, security, observability, evaluation, and guardrails
- Ensure engagements are delivered on time, within scope, and with measurable business value
- Shape architectural standards for building and deploying agentic capabilities and accelerators
- Establish the foundation of the India Agentic Delivery Center by developing scalable patterns, tooling, and ways of working
- Collaborate with forward-deployed engineers, data scientists, data engineers, platform/DevOps engineers, and business stakeholders
- Ensure quality through code reviews, documentation, testing, governance, and adherence to security and compliance standards
- Partner with practice and account leaders to expand engagements, improve delivery, and standardize AI deployment and operations
- Contribute to IP development, accelerators, reference architectures, templates, playbooks, and AI engineering training
- Act as a trusted advisor to senior client stakeholders, shaping roadmaps and strategic decisions
- Mentor and coach team members
- Define and refine practice standards, reusable assets, and delivery frameworks
Requirements:
- 6+ years of experience as an AI Engineer, Machine Learning Engineer, Software Engineer, or Data Engineer building and deploying production AI/ML solutions, including recent hands-on experience with LLM-powered or agentic applications
- Hands-on understanding of Large Language Models, agentic architectures, retrieval frameworks (RAG), prompt design, context engineering, and tool/function calling
- Experience with LLM orchestration frameworks such as LangChain and LlamaIndex, plus multi-agent patterns, memory, planning, and protocols such as MCP
- Experience designing evaluation, guardrail, and observability strategies for LLM and agent systems (LLMOps/AgentOps)
- Hands-on experience with modern programming languages such as Python, including API development
- Deep expertise in cloud-native AI/ML platforms such as AWS Bedrock, SageMaker, Azure AI/ML, and Snowflake Cortex, with production deployment experience
- Complete software development lifecycle experience covering design, documentation, implementation, testing, deployment, and ongoing operations
- Demonstrated use of AI-assisted development tooling
- Strong working knowledge of SQL and ability to write, debug, and optimize complex distributed queries
- Experience delivering projects for external or internal clients in professional services or consulting, ideally fixed-bid
- Ability to break down ambiguous problems into structured, actionable steps
- Excellent written and verbal communication in English, including presenting technical solutions to clients and facilitating technical and business discussions
- Ability to work effectively with distributed, cross-functional teams across the US, LATAM, and India
- Proven ownership, prioritization, and delivery of high-quality work with minimal supervision
- Bachelor’s degree in Computer Science or a related technical field, or equivalent practical experience is preferred, not required
Benefits:
- Remote-First Workplace
- Medical Insurance for Self & Family
- Medical Insurance for Parents
- Term Life & Personal Accident
- Wellness Allowance
- Broadband Reimbursement
- Continuous learning and growth opportunities to enhance your skills and expertise
- Paid certifications
- Professional development allowance
- Bonuses for creating company-approved content
- Challenging projects, mentorship, and structured development pathways
- Supportive, high-performing global team
- Transparency, autonomy, and continuous improvement
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