AI Engineer Data & AI

Power Tech Consulting Pty Ltd.; Bengaluru; Hybrid; INR 4,000,000 - 8,000,000; Full time

Job summary

Power Tech Consulting Pty Ltd. in Bengaluru at the Bangalore hybrid site seeks an AI Engineer (FastAPI & AWS) to design, build, and scale production-grade REST APIs exposing AI capabilities for enterprise clients.

The role emphasizes hands-on engineering across the full API lifecycle on FastAPI, Pydantic, and AWS, with collaboration across data engineers and AI researchers. The candidate will own schema design, endpoint implementation, deployment, and scaling on AWS while ensuring secure,

Qualifications

• Strong Python backend skills with async design for high concurrency.
• Production experience building REST APIs with FastAPI and Pydantic models.
• Hands-on AWS Bedrock and hosting on EC2/Lambda/EMR.
• Experience with API security, authentication, and rate limiting.
• Cloud-native deployment and containerisation with Docker.

Responsibilities

• Design and build RESTful AI APIs with full CRUD endpoints.
• Define request/response schemas using Pydantic, ensure validation and serialization.
• Integrate AWS Bedrock LLMs behind versioned API contracts.
• Deploy, scale, and monitor API services on AWS EC2/Lambda and EMR.
• Implement security, CI/CD, logging, and observability for production APIs.
• Collaborate with data engineers and AI researchers to deliver scalable pipelines.

Skills

Python

Async IO

REST APIs

FastAPI

Pydantic

AWS Bedrock

AWS EC2

AWS Lambda

OAuth2

JWT

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

AWS

EC2

Lambda

EMR

OpenAPI/Swagger

LangChain

Pinecone/FAISS

Kubernetes

Job description

About the role

Ahands-on engineering role. You'll design, build, and scale production-gradeREST APIs that expose AI and LLM capabilities to our enterprise and governmentclients, owning the full API lifecycle on FastAPI, Pydantic, and AWS.

AI Engineer (FastAPI & AWS)

At a Glance

• Location: Bangalore, India (Hybrid)
• Employment type: Full-time permanent
• Experience: Mid to senior level, over 10 years,including production FastAPI and AWS experience
• Role type: Hands-on engineering, not apeople-management role
• Core focus: FastAPI and Pydantic REST APIs,AWS Bedrock LLM integration, and scalable deployment on EC2, Lambda, and EMR

AboutPower Tech Consulting

Power Tech is a data, AI, cloud, andtransformation consultancy serving mining, financial services, hospitality, andgovernment clients across Australia, New Zealand, Fiji, Singapore, and India.We're multi-vendor, so we recommend what's right, not what's easy to sell, andwe're building our own products alongside client work.

Service through contribution. Trustthrough transparency. Accountable from end to end. Join us and help shape whatPower Tech becomes.

Aboutthe Role

Our clients increasingly want AIcapabilities they can rely on in production, delivered through fast, secure,well-documented services. As AI Engineer (FastAPI & AWS), you'll own thefull API lifecycle, from schema design and endpoint implementation todeployment and scaling on AWS. You'll work alongside our data engineers,architects, and applied-AI research team.

Key Responsibilities

• Design and build RESTful AI APIs in FastAPI,implementing full CRUD resources (GET, POST, PUT, PATCH, and DELETE).
• Define request and response schemas,validation, and serialisation using Pydantic models.
• Integrate AWS Bedrock foundation models andother LLM services behind clean, versioned API contracts.
• Design async, non-blocking endpoints forhigh-throughput and streaming AI workloads.
• Deploy and scale API services on AWS EC2 andLambda, including auto-scaling and load-balancing configuration.
• Build and orchestrate data-processingworkflows on AWS EMR to support AI pipelines.
• Implement authentication, authorisation,rate-limiting, and API versioning, using OAuth2, JWT, and API keys.
• Write automated unit, integration, and loadtests, and maintain OpenAPI and Swagger documentation.
• Implement caching, connection pooling, andperformance tuning so APIs stay scalable and low-latency.
• Set up CI/CD, logging, monitoring, andobservability for API services in production.

Must-HaveSkills and Experience

• Strong Python and backendsoftware-engineering fundamentals, including async Python (asyncio,async/await) for high-concurrency API design.
• Hands-on production experience building RESTAPIs with FastAPI, including full CRUD endpoint design.
• Strong command of Pydantic for datavalidation, schema modelling, and serialisation.
• Hands-on experience with AWS Bedrock forgenerative AI and LLM integration.
• Practical experience with AWS EC2, Lambda,and EMR for hosting and scaling API and data workloads.
• Experience with API security, authenticationand authorisation, and rate-limiting patterns.
• Experience with cloud-native deployment,containerisation with Docker, and infrastructure-as-code.
• Understanding of API scalability patterns:load balancing, caching, horizontal scaling, and queuing.

DesirableSkills

• Experience with GenAI frameworks such asLangChain, LangGraph, or CrewAI, and with RAG architectures.
• Familiarity with vector databases such asPinecone, FAISS, or pgvector.
• AWS API Gateway experience, and event-drivenarchitectures using SQS, SNS, or EventBridge.
• MLOps or LLMOps tooling and model monitoring.
• AWS certifications such as AWS Certified AIPractitioner or Solutions Architect, and responsible-AI or AI-governanceexperience.

Education

• A bachelor's degree in computerscience, engineering, or a related field, or equivalent experience.

WhatSuccess Looks Like

• The AI APIs you build run reliably inproduction, meeting their latency and throughput targets as client usage grows.
• Your API contracts are clean, versioned, andwell documented, so client and internal teams can integrate withouthand-holding.
• Security, testing, and observability arebuilt into your services from the start, not added after an incident.
• Your patterns for FastAPI, Pydantic, andBedrock become reusable building blocks across our AI engagements.