Role: Applied AI Engineer

Job type: FT with Highspring

Shift: 2 to 11 pm IST

Location: 100% remote

Applied AI Engineer

Role Overview

We are looking for an Applied AI Engineer to design production-grade autonomous agentic systems while maintaining and optimizing our existing traditional machine learning pipelines. In this role, you will balance cutting-edge LLM orchestration with the upkeep of algorithm-heavy legacy workflows, including

OCR systems.

Key Responsibilities

- Develop Agentic Workflows: Build autonomous multi-agent systems, cognitive loops, and

reasoning workflows utilizing tool execution and self-correction.
- Maintain Traditional ML & OCR: Support, optimize, and scale existing algorithmic pipelines, with

a specific focus on Optical Character Recognition (OCR) and heavy backend processing algorithms.
- Production Deployment: Ship both generative and traditional AI prototypes into scalable, low-

latency production environments.
- State & Memory Management: Design robust state machines to handle agent memory, context,

and multi-step persistence.
- Optimize & Evaluate: Implement frameworks to monitor model behavior, mitigate

hallucinations, and optimize compute/token spend.

Technical Qualifications

Core Fundamentals

- Software Engineering: Strong command of Object-Oriented Programming (OOP), data

structures, and clean code architecture.
- Machine Learning: Solid grounding in core ML fundamentals, including supervised/unsupervised

learning algorithms, and traditional computer vision/OCR techniques. Required AI & Python Expertise
- Python:



4+ years of professional experience (strong focus on asynchronous programming,

Pydantic, and FastAPI).
- Agentic AI Frameworks: Hands-on experience with LangGraph, Strands SDK, CrewAI, or building

custom agent loops.
- LLM Orchestration: Mastery of advanced prompt engineering, function calling, and complex

Retrieval-Augmented Generation (RAG) patterns.
- MCP server and client implementations

Preferred
- Implementing cloud-native solutions on AWS and hands-on exposure of building production

workloads with: AWS Bedrock: Provisioning, fine-tuning, and orchestrating foundational models.

AWS Lambda: Building event-driven architecture and executing isolated agent tools.

AWS DynamoDB: Managing session persistence, agent memory states, and fast transactional storage.

- Vector Architecture: Familiarity with vector databases (e.g., OpenSearch, FAISS) for knowledge

retrieval.
- Experience with API and Micro-services implementations

Notes from the hiring manager - He is looking for a proven engineer whose deliverables we can vouch for. Experience with up-to-date AWS stack and traditional ML is a must. Hiring an unknown entity with unverified credentials may cause a lot of delay in ramp up. He mentioned it can take up to 2 years before they start delivering something meaningful.

Projects include enhancing existing product line and building new ones.

He is not looking for folks who have done only Agentic AI work. He is looking for hands on experience with traditional Machine Language and Optical Character Recognition (OCR) experience.

📌 Applied AI Engineer (Delhi)
🏢 Highspring India
📍 Delhi