Senior Applied AI Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Develop and implement comprehensive agentic AI solutions, encompassing RAG pipelines, multi-agent workflows, and human-in-the-loop elements for enterprise clients.

• Convert solution designs and business requirements into clean, well-tested production-level code.

• Create dependable, scalable, secure, observable, assessed, and safeguarded production-grade agents.

• Deliver projects punctually, within defined scope, and with quantifiable business impact.

• Contribute to the development of reusable agentic accelerators and reference implementations.

• Assist in establishing engineering patterns, tools, and operational methodologies for the India delivery center.

• Collaborate effectively with forward-deployed engineers, data engineers, platform/DevOps engineers, and business stakeholders.

• Maintain deliverable quality through code reviews, technical documentation, automated testing, and adherence to security and governance standards.

• Work alongside practice and account leaders to broaden engagements and standardize AI deployment methodologies.

• Contribute to the development of intellectual property, architectures, templates, playbooks, and training for colleagues.

• Represent phData professionally with both technical and non-technical stakeholders.

⛳️ Requirements

• 4+ years of experience in AI/ML engineering, software engineering, or data engineering roles focused on building and deploying AI/ML solutions into production.

• Recent hands-on experience with LLM-powered or agentic applications.

• Knowledge 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.

• Proven experience in designing evaluation, guardrail, and observability strategies for LLM and agent systems.

• Hands-on proficiency with modern programming languages like Python, including API development.

• Extensive knowledge of cloud-native AI/ML platforms such as AWS Bedrock, SageMaker, Azure AI/ML, and Snowflake Cortex.

• Complete understanding of the software development lifecycle.

• Demonstrated use of AI-assisted development tools.

• Strong working knowledge of SQL, including complex and distributed query writing, debugging, and optimization.

• Experience in delivering projects for external or internal clients in professional services, product, or consulting environments.

• Ability to deconstruct complex problems into actionable steps, ideally in a fixed-bid context.

• Excellent written and verbal communication skills in English.

• Proven experience in presenting solutions and collaborating directly with clients.

• Capability 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 oversight.

• Comfort in working within 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: experience with reusable accelerators, modular codebases, or multi-client products.

• Preferred: AI/ML industry experience in life sciences, retail, financial services, or manufacturing.

• Preferred: experience with global or remote teams.

• Preferred: contributions to open source, technical communities, speaking engagements, or technical writing.

• A 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 company-approved content.

• Engaging projects, mentorship, and structured development pathways.

• Supportive, high-performing global team.

• Transparency, autonomy, and a culture of continuous improvement.