Senior Associate AI Engineer

Emplay; United States; Remote; USD 170,000 - 250,000; Full time

Job summary

Emplay is seeking a Senior AI Engineer to design and deliver production-grade, LLM-powered features on AWS. You will build intelligent agents, optimize RAG pipelines, and collaborate with cross-functional teams to ship high-quality AI solutions at scale.

The role requires hands-on experience with LLM APIs (AWS Bedrock, OpenAI, Anthropic), LangChain, and multi-region AWS architectures, plus strong Python backend skills and API design capabilities.

Qualifications

• 2–3 years of experience in AI/ML engineering or related technical role.
• Hands-on experience with LLM APIs — AWS Bedrock, OpenAI, or Anthropic — and production GenAI features.
• Strong knowledge of RAG pipeline design — embeddings, vector stores (OpenSearch, Pinecone, pgvector).
• Proficiency with LangChain or LlamaIndex; familiarity with MCP (Model Context Protocol).
• Solid AWS skills — Lambda, ECS/EKS, S3, DynamoDB, OpenSearch, SQS, and multi-region architecture patterns.
• Backend development in Python (FastAPI/Flask) — production services and APIs.
• REST / GraphQL API design with OpenAPI; OAuth 2.0, SAML, and OIDC.
• Infrastructure-as-code experience using Terraform or AWS CDK; CI/CD pipelines with GitHub Actions or equivalent.
• Strong problem-solving skills and ability to work with ambiguous requirements.
• Good communication skills, able to work with both technical and non-technical stakeholders.

Responsibilities

• Design, build, and deploy LLM-powered agents and conversational AI features on AWS.
• Architect and optimise end-to-end RAG pipelines — embedding, vector indexing, and context retrieval.
• Implement Model Context Protocol (MCP) servers to support multi‑agent orchestration workflows.
• Develop and maintain LLM evaluation frameworks for quality assurance and regression tracking.
• Build scalable, multi‑region cloud infrastructure leveraging core AWS services.
• Secure APIs and enforce access controls, authentication flows, and data privacy standards.
• Integrate third‑party platforms (CRM, Sales Enablement, analytics tools) via REST APIs and webhooks.
• Build bulk data ingestion/export pipelines and instrument usage analytics and logging.
• Own CI/CD pipelines, automated regression testing, and production reliability.
• Collaborate with product and engineering teams to scope, estimate, and deliver features on time.

Skills

AI/ML engineering

Python development

REST API design

Communication skills

Problem solving

Tools

LangChain

LlamaIndex

AWS Bedrock

OpenAI

Anthropic

OpenSearch

Pinecone

pgvector

Terraform

AWS CDK

GitHub Actions

S3

DynamoDB

ECS/EKS

Lambda

SQS

Job description

We are looking for a Senior AI Engineer with hands‑on experience in Generative AI, Retrieval‑Augmented Generation (RAG), and AWS cloud services. You will design and deliver production‑grade LLM‑powered features, build intelligent agents, and integrate enterprise tools — working closely with cross‑functional teams to ship high‑quality AI solutions at scale.

Key Responsibilities

• Design, build, and deploy LLM‑powered agents and conversational AI features on AWS.
• Architect and optimise end‑to‑end RAG pipelines — embedding, vector indexing, and context retrieval.
• Implement Model Context Protocol (MCP) servers to support multi‑agent orchestration workflows.
• Develop and maintain LLM evaluation frameworks for quality assurance and regression tracking.
• Build scalable, multi‑region cloud infrastructure leveraging core AWS services.
• Secure APIs and enforce access controls, authentication flows, and data privacy standards.
• Integrate third‑party platforms (CRM, Sales Enablement, analytics tools) via REST APIs and webhooks.
• Build bulk data ingestion/export pipelines and instrument usage analytics and logging.
• Own CI/CD pipelines, automated regression testing, and production reliability.
• Collaborate with product and engineering teams to scope, estimate, and deliver features on time.

Qualifications

• 2–3 years of experience in AI/ML engineering or a related technical role, preferably in SaaS or a cloud‑native environment.
• Hands‑on experience with LLM APIs — AWS Bedrock, OpenAI, or Anthropic — and building production‑ready GenAI features.
• Strong knowledge of RAG pipeline design — embeddings, vector stores (OpenSearch, Pinecone, pgvector),and retrieval strategies.
• Proficiency with agent frameworks such as LangChain or LlamaIndex; familiarity with MCP (Model Context Protocol).Solid AWS skills — Lambda, ECS/EKS, S3, DynamoDB, OpenSearch, SQS, and multi‑region architecture patterns.
• Backend development in Python (FastAPI / Flask) — able to write and maintain production‑quality services and APIs.
• REST / GraphQL API design with OpenAPI documentation; experience with OAuth 2.0, SAML, and OIDC.
• Infrastructure‑as‑code experience using Terraform or AWS CDK; CI/CD pipelines with GitHub Actions or equivalent.
• Strong problem‑solving skills and ability to work with ambiguous requirements.
• Good communication skills, able to work with both technical and non‑technical stakeholders.

Preferred Skills

• Experience with Sales Enablement or CRM integrations
• Familiarity with advanced agent orchestration and multi‑tool LLM workflows.
• Prior experience in a B2B SaaS or enterprise software environment.