Senior Applied AI Engineer
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Job Description
Senior Applied AI Engineer building production-ready agentic AI solutions for phData, a data and AI consultancy. Delivering RAG pipelines, multi-agent workflows, and enterprise integrations for measurable client outcomes.
Responsibilities:
- Build and operationalize end-to-end agentic AI solutions, including RAG pipelines, multi-agent workflows, and human-in-the-loop steps, for enterprise clients
- Translate solution designs and business requirements into clean, well-tested production-grade code
- Build reliable, scalable, secure, observable, evaluated, and guarded production-grade agents
- Deliver engagements on time, within scope, and with measurable business value
- Contribute to reusable agentic accelerators and reference implementations
- Help establish engineering patterns, tooling, and ways of working for the India delivery center
- Collaborate with forward-deployed engineers, data engineers, platform/DevOps engineers, and business stakeholders
- Ensure deliverable quality through code reviews, technical documentation, automated testing, and security and governance standards
- Partner with practice and account leaders to expand engagements and standardize AI deployment approaches
- Contribute to IP development, architectures, templates, playbooks, and colleague training
- Represent phData professionally with technical and non-technical stakeholders
Requirements:
- 4+ years of experience in AI/ML engineering, software engineering, or data engineering roles building and deploying AI/ML solutions to production
- Recent hands-on experience with LLM-powered or agentic applications
- Understanding of LLMs, agentic architectures, RAG, prompt design, context engineering, and tool/function calling
- Experience with LangChain, LlamaIndex, multi-agent patterns, memory, planning, and protocols such as MCP
- Experience designing evaluation, guardrail, and observability strategies for LLM and agent systems
- 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
- Complete software development lifecycle experience
- Demonstrated use of AI-assisted development tooling
- Strong working knowledge of SQL, including complex and distributed query writing, debugging, and optimization
- Experience delivering projects for external or internal clients in professional services, product, or consulting environments
- Ability to break down complex problems into actionable steps, ideally in a fixed-bid capacity
- Strong written and verbal communication skills in English
- Proven experience presenting solutions and working directly with clients
- Ability to work effectively with distributed cross-functional teams across the US, LATAM, and India
- Track record of ownership, managing multiple priorities, and delivering high-quality work with minimal supervision
- Comfort working in client environments and adapting solutions to existing architectures and processes
- Bachelor’s degree in Computer Engineering, Computer Science, or a related technical field, or equivalent practical experience preferred
- Preferred: reusable accelerators, modular codebases, or multi-client products experience
- Preferred: AI/ML industry experience in life sciences, retail, financial services, or manufacturing
- Preferred: global or remote team experience
- Preferred: open source, technical community, speaking, or technical writing contributions
- Master’s or other advanced degree is a plus
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 for company-approved content
- Challenging projects, mentorship, and structured development pathways
- Supportive, high-performing global team
- Transparency, autonomy, and continuous improvement
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