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 moments 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 years

Location : 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 platformspanning 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 :

1. RAG architectures

2. Embeddings & vector search

3. 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.