AI/ML Engineer (AI Platform & Backend Engineering)

Location: Kothrud, Pune (On-site)

Experience: 2–4 Years

Employment Type: Full-Time

Build AI Products.

Own Your

Work.

Scale Intelligent

Systems. At SwayAlgo Technologies, we build AI-powered products, enterprise platforms, intelligent web applications, and automation solutions.

Our engineers don't just integrate AI APIs—they build scalable AI platforms, solve complex engineering challenges, and create production-ready systems that power real-world applications.

We're looking for an AI/ML Engineer who combines strong AI engineering expertise with solid backend engineering skills. This role is AI/ML Engineering and Backend & Platform Engineering, focused on building reliable, scalable, and cost-efficient AI systems.

If you enjoy working with the latest AI models, designing production AI infrastructure, and building end-to-end intelligent systems, we'd love to meet you.

What You'll Build You'll contribute to a variety of AI-powered product initiatives, including:

AI-powered applications

Enterprise AI solutions

Intelligent automation systems

Multimodal AI applications

AI APIs and backend services

Scalable AI platforms and infrastructure

You'll work closely with frontend, backend, DevOps, and product teams to build production-ready AI systems used by real customers.

Key Responsibilities

AI Engineering

Generative AI

Build production-ready applications using Large Language Models (LLMs).

Work with image generation and video generation AI models.

Build multimodal AI workflows combining text, images, documents, and structured data.

Design AI processing pipelines covering preprocessing, inference, post-processing, and response generation.

Implement prompt engineering, prompt optimization, prompt versioning, and prompt caching.

Integrate multiple AI providers and foundation models.

AI Platform Engineering

Design and build the core AI platform powering production AI workloads.

Responsibilities include

AI runtime routing across multiple providers and models

Model selection based on latency, quality, availability, and cost

AI request orchestration

Prompt caching and semantic caching

AI response caching

Token consumption tracking

AI usage analytics

Cost calculation and optimization

Budget monitoring and quota management

Retry and fallback strategies

AI provider failover

AI evaluation pipelines

Automated response scoring

AI quality benchmarking

Model comparison and A/B testing

AI observability, logging, tracing, and monitoring

AI Performance & Scalability

Design AI services capable of handling high-concurrency production workloads.

Optimize inference latency, throughput, reliability, and infrastructure costs.

Implement batching, streaming, asynchronous inference, and background processing.

Build scalable AI services using queues, caching, and distributed architectures.

Continuously optimize model performance and operational costs.

Backend & Platform Engineering

Backend Engineering

Build scalable backend services using Python, FastAPI, and gRPC.

Design modular microservices and production-ready APIs.

Build secure authentication, authorization, and API security.





Develop event-driven and asynchronous processing systems.

Write clean, maintainable, and production-quality code.

Data Engineering

Design scalable PostgreSQL database schemas.

Optimize SQL queries, indexing, and transactions.

Build Redis-based caching layers.

Implement queue mechanisms, distributed locking, and background workers.

Develop efficient preprocessing and ingestion pipelines.

Infrastructure & DevOps

Containerize AI services using Docker.

Build and maintain CI/CD pipelines.

Deploy AI workloads on cloud infrastructure.

Monitor production systems using logs, metrics, and tracing.

Design highly available, fault-tolerant, and scalable AI infrastructure.

Optimize compute, GPU utilization, and cloud costs.

Product Ownership

Understand business problems before designing AI solutions.

Participate in architecture and technical design discussions.

Build AI features end-to-end from design and development to deployment and monitoring.

Take ownership of scalability, reliability, security, quality, and operational costs.

Continuously improve AI systems based on performance metrics and customer feedback.

Required Skills

AI & Generative AI

Robust hands-on experience with:

Large Language Models (LLMs)

Prompt Engineering

Prompt Optimization

Prompt Caching

AI Processing Pipelines

Image Generation Models

Video Generation Models

Multimodal AI

AI Evaluation

AI Runtime Optimization

Token Consumption Analysis

Cost Optimization

AI Provider Integration

AI Platforms

Hands-on experience with one or more:

Google Vertex AI

AWS Bedrock

Azure AI Foundry

Experience building vendor-agnostic AI applications across multiple providers is highly preferred.

Backend Engineering

Strong experience with

Python

FastAPI gRPC

REST APIs

Microservices

Distributed Systems

Asynchronous Programming

PostgreSQL

Redis

Queue Mechanisms

Caching Strategies

Docker

Infrastructure & DevOps

Experience with

Docker

Git

Linux

CI/CD

Cloud Platforms (AWS, GCP, Azure)

Monitoring & Observability

Production Deployments

Good understanding of

Kubernetes

High-Concurrency Systems

Load Balancing

Rate Limiting

Fault Tolerance

Distributed Architectures

Performance Optimization

Software Engineering

Strong understanding of

Clean Architecture

Design Patterns

System Design

API Design

Debugging

Performance Profiling

Logging

Testing

Secure Coding Practices

Preferred Skills

Experience with any of the following is a strong advantage:

LangGraph

LangChain

LlamaIndex

Model Context Protocol (MCP)

AI Agents

Workflow Orchestration

Vector Databases (PGVector, Milvus, Pinecone, Weaviate)

RabbitMQ, Kafka, NATS, Celery, BullMQ

WebSockets

GraphQL

Object Storage (S3, GCS)

Prometheus

Grafana

OpenTelemetry

Kubernetes

OCR

Computer Vision

Document AI

Open-source contributions,



AI research, production AI systems, or personal AI products are highly valued.

Who We're Looking For

We're looking for engineers who:

Have a product mindset and think beyond model integration.

Are strong AI engineers with solid backend engineering skills.

Understand how to build scalable, reliable, and cost-efficient AI platforms.

Can optimize AI quality, latency, throughput, and operational costs.

Are self-managed, proactive, and accountable.

Can build features end-to-end with minimal supervision.

Take ownership instead of waiting for instructions.

Enjoy solving complex engineering and AI infrastructure challenges.

Thrive in a fast-paced startup environment.

Want to become part of a long-term core engineering team.

Why Join SwayAlgo?

You'll work on

AI-powered Applications

Enterprise AI Solutions

Generative AI Systems

Multimodal AI Applications

AI Platform Engineering

Scalable AI Infrastructure

Modern Backend Architecture

End-to-End Product Development

You'll work directly with founders and experienced engineers, contribute to platform architecture, and build AI systems that power real-world products.

Our Engineering Culture

We value engineers who

Think like product builders.

Own problems, not just tasks.

Build scalable systems with long-term thinking.

Continuously learn and experiment with emerging AI technologies.

Balance AI quality, latency, scalability, reliability, and cost.

Collaborate openly and support teammates.

Use AI responsibly while maintaining strong engineering fundamentals.

Take pride in building production-ready products with real-world impact.

Who Should Apply

You'll thrive if you

Love building AI products—not just AI demos.

Enjoy backend engineering and AI infrastructure.

Like solving scalability and performance challenges.

Want ownership and technical freedom.

Are looking for long-term growth in a product-focused startup.

Who Should Not Apply

This role isn't for you if you:

Only have experience calling AI APIs without building production systems.

Prefer research-only work without shipping products.

Avoid ownership or production responsibility.

Are uncomfortable with ambiguity or rapid iteration.

Are looking for a short-term role instead of helping build a company.

Hiring Process

Resume Screening

Screening Interview (Technical + Cultural Fit)

Technical Interview

HR Discussion

Offer

How to Apply

If you're passionate about building scalable AI systems, modern backend platforms, and production-ready AI applications, we'd love to hear from you.

Send your application to: [email protected]

Please include

Resume (PDF)

GitHub Profile

Portfolio or AI Projects (if available)

LinkedIn Profile

Email Subject

Application – AI/ML Engineer – Your Name

Join Our Core Team

At SwayAlgo Technologies, we're building more than AI features—we're building scalable AI products and platforms for the future. If you're passionate about Generative AI, AI Platform Engineering, backend systems, scalability, and building products end-to-end, and want to grow as part of a long-term core engineering team, we'd love to build the future with you.

📌 AI/ML Engineer (AI Platform & Backend Engineering) (Pune)
🏢 Swayalgo Technologies
📍 Pune