TaskUsAI Architect / Lead Engineer (Agentic AI Platform)
About TaskUs: TaskUs is a provider of outsourced digital services and next-generation customer experience to fast-growing technology companies, helping its clients represent, protect and grow their brands. Leveraging a cloud-based infrastructure, TaskUs serves clients in the fastest-growing sectors, including social media, e-commerce, gaming, streaming media, food delivery, ride-sharing, HiTech, FinTech, and HealthTech.
The People First culture at TaskUs has enabled the company to expand its workforce to approximately 45,000 employees globally. Presently, we have a presence in twenty-three locations across twelve countries, which include the Philippines, India, and the United States.
It started with one ridiculously good idea to create a different breed of Business Processing Outsourcing (BPO)! We at TaskUs understand that achieving growth for our partners requires a culture of constant motion, exploring new technologies, being ready to handle any challenge at a moment’s notice, and mastering consistency in an ever-changing world.
What We Offer: At TaskUs, we prioritize our employees' well-being by offering competitive industry salaries and comprehensive benefits packages. Our commitment to a People First culture is reflected in the various departments we have established, including Total Rewards, Wellness, HR, and Diversity. We take pride in our inclusive environment and positive impact on the community. Moreover, we actively encourage internal mobility and professional growth at all stages of an employee's career within TaskUs. Join our team today and experience firsthand our dedication to supporting People First.
Role: AI Architect / Lead Engineer (Agentic AI Platform)Experience: 7–15 yearsLocation: Flexible / Hybrid
About the Role:
We are building a Hybrid Agentic AI Platform that runs across AWS, multi-cloud, and customer environments (VPC/on-prem). This role will own the end-to-end architecture AND implementation of the platform—spanning data ingestion, context building (RAG), agent orchestration, QA automation, and secure enterprise deployment.
This is a builder-first leadership role: you will design systems, write production code, and guide a small team to deliver a scalable, privacy-first AI platform.
Responsibilities
Architecture & System Design
Define end-to-end architecture: ingestion → processing → RAG → agents → QA scoring → insights
Design hybrid deployment models (SaaS, in-VPC, on-prem)
Establish patterns for multi-tenancy, isolation, and scalability
Make key build vs buy decisions (LLMs, vector DBs, orchestration)
AI / Agentic Systems
Design and implement agent orchestration frameworks
Build RAG pipelines (chunking, embeddings, retrieval, re-ranking)
Integrate LLMs (managed/private) with no-retention and guardrails
Define evaluation frameworks (quality, hallucination checks, QA scoring)
Security & Data Privacy
Implement data-in-place architectures (compute-to-data, VPC access)
Design for PII handling, masking, and auditability
Ensure compliance-ready patterns (SOC2, GDPR-style controls)
Platform Engineering
Build core services/APIs powering workflows and integrations
Design event-driven and microservices architectures
Ensure reliability, observability, and performance at scale
Team Leadership
Lead and mentor engineers (AI, data, backend, FDE)
Set coding standards, architecture principles, and best practices
Work closely with customers on complex deployments when needed
Required Skills
Core Engineering
Strong programming in Python (plus Node.js/Java is a bonus)
Deep experience with distributed systems & system design
Hands-on with APIs, microservices, and event-driven systems
AI / GenAI
Production experience with LLMs / GenAI systems
Strong understanding of:
RAG architectures
Embeddings & vector search
Prompting and agent workflows
Experience with LLM platforms (AWS Bedrock, open-source models, etc.)
Cloud & Platform
Deep experience with AWS (VPC, IAM, Lambda, ECS/EKS, S3)
Experience designing secure enterprise deployments
Familiarity with Docker, Kubernetes, Terraform
Nice to Have
Experience with agent frameworks (LangChain, LangGraph, etc.)
Multi-cloud experience (Azure/GCP)
Experience with contact center / QA automation domains
Knowledge of data engineering pipelines
Exposure to LLM evaluation and guardrails frameworks
What Makes You a Great Fit
You are equally comfortable whiteboarding architecture and writing code
You have built 0→1 systems and scaled them
You make pragmatic decisions, not over-engineered ones
You thrive in ambiguity and move fast with ownership
Impact
Define and build the core platform architecture
Accelerate MVP → production for enterprise customers
Establish the technical foundation for a category-defining AI platform
Success in 90 Days
Designed and validated reference architecture
Built core RAG + agent orchestration pipeline
Enabled first customer deployment (VPC or hybrid)
Established engineering standards and velocity
What This Role Is Not
Not a pure architect who only creates diagrams
Not a research-only AI/ML role
Not detached from customers or real-world constraints
This is a hands-on builder-leader role
How We Partner To Protect You: TaskUs will neither solicit money from you during your application process nor require any form of payment in order to proceed with your application. Kindly ensure that you are always in communication with only authorized recruiters of TaskUs.
DEI: In TaskUs we believe that innovation and higher performance are brought by people from all walks of life. We welcome applicants of different backgrounds, demographics, and circumstances. Inclusive and equitable practices are our responsibility as a business. TaskUs is committed to providing equal access to opportunities. If you need reasonable accommodations in any part of the hiring process, please let us know.
We invite you to explore all TaskUs career opportunities and apply through the provided URL https://www.taskus.com/careers/.