Senior Backend Engineer

About the role

We are seeking an AI Engineer to build and implement AI systems for content production at scale. You'll work at the intersection of engineering and content designing prompt pipelines, integrating generative models, and building the tooling that turns source material into finished creative output. The ideal candidate is technically strong but also has taste: someone who understands story and craft, and can tell the difference between output that's technically correct and output that's actually good.

Responsibilities

• Build and iterate on prompt pipelines and multi-agent workflow components
• Design and integrate agentic workflows orchestrate multi-step, tool-using agents that plan, call models, and hand off between stages in production
• Deploy and serve open-source models set up inference endpoints, manage GPU compute, and optimize for latency and cost
• Write evals compare outputs against references, quantify quality, and feed results back into the pipeline
• Work on data pipelines: structured extraction from messy source text, localization, similarity/dedup
• Debug and maintain pipeline stages in production

What you bring:  

• (1+/3+) years of engineering experience, or a strong portfolio of shipped projects
• Solid Python fundamentals clean, working, readable code
• Hands-on experience with LLM APIs and prompt engineering (personal projects count)
• Comfort with Git, REST APIs, and working in a Linux environment
• A feel for content and narrative you can judge whether generated output is actually good, not just valid
• Curiosity and clear communication you ask good questions and don't stay stuck silently

 Preferred

• Exposure to agent/orchestration frameworks (LangGraph, LangChain, CrewAI)
• Familiarity with vector databases, embeddings, or RAG (Qdrant, pgvector)
• Hands-on work with open-source generative media models Flux, LTX, Wan, or similar
• Experience deploying open-source models for inference (vLLM, ComfyUI, Replicate/Cog, Docker + GPU)
• Experience writing evals or LLM-as-judge scoring
• Node.js and Fastapi familiarity, or experience deploying on AWS

Job Description: Python Developer

Experience: 2+ Years

Job Location: Nr. Iskcon Mega Mall, SG Highway, Ahmedabad

Timings: 10 AM to 7 PM

Job Description:

Technical Skills :

• Good knowledge of Python with 2+ years of minimum experience 
• Strong understanding of various Python Libraries, APIs, and toolkits. 
• Good experience in Django, Django REST Framework, and Flask framework.
• Understanding of AWS Serverless implementation using Lambda and API Gateway
• Hands-on Experience in Databases like Mysql, PostgreSQL.
• Good experience/understanding in Agentic AI / RAG.
• Proficient in NoSQL document databases especially MongoDB, Redis.
• Stronghold in Data Structures and Algorithm
• Thorough understanding of version control system concepts especially GIT.
• Understanding of the whole web stack and how all the pieces fit together (front-end, database, network layer, etc.) and how they impact the performance of your application.
• Excellent understanding of MVC and OOP. Bonus for the understanding of prevalent design patterns.
• Excellent debugging and optimization skills

Job Responsibilities :

• Building big, robust, scalable, and maintainable applications.
• Debugging, Fixing bugs, Identifying Performance Issues, and Improving App Performance.
• Continuously discover, evaluate, and implement new technologies to maximize development efficiency.
• Handling complex technical issues related to web app development & discussing solutions with the team.
• Developing, Deploying, and maintaining Multistage, Multi-tier applications.
• To write high-performing code and will be participating in key architectural decisions.
• Project Execution & Client Interaction
• Scrum Implementation

Role & Responsibilities

As a Senior GenAI Engineer you will own the AI layer of our product — building the features that make Zenskar intelligent. This is not a research role and not a prompt-engineering role. You will build production AI systems that enterprise clients depend on, which means reliability, observability, and rigorous evals matter as much as the AI capability itself. You own the full vertical — the model, the pipeline, and the UI.

• Build and own CS Copilot — a real-time assistant for customer success teams, spanning STT pipelines, live transcription, and LLM-powered suggestions
• Build LLM-powered document understanding features — extracting structured, reliable data from unstructured enterprise documents
• Own AI feature UIs end-to-end — you build the interface, not just the model integration layer
• Design and maintain an eval framework — define what 'working' means for each AI feature and catch regressions before users do
• Drive model selection and integration decisions — choosing the right provider and approach for each use case, managing latency and cost
• Own AI platform reliability — observability, fallback behaviour, and graceful degradation when models fail
• Work closely with product, customer success, and the full-stack engineer — AI features only matter if they are usable and trusted by real users

THE IMPACT YOU'LL MAKE-

• You will define what AI means at Zenskar — the features you ship will be the most visible and differentiated parts of the product
• CS Copilot, if done well, changes how enterprise customer success teams operate every single day — this is a high-stakes, high-visibility surface
• You will establish the engineering culture around AI reliability at Zenskar — evals, observability, and disciplined iteration
• Your work will directly accelerate enterprise deals — AI features are increasingly a buying criterion for our clients
• You will be the person who brings engineering rigour to a domain where most companies ship demos and call it a feature

Ideal Candidate

• Strong Senior GenAI / AI Backend Engineer Profiles
• Mandatory (Experience 1) – Must have 4+ years of total software development experience, with at least 2+ years working on AI/LLM-based features in production
• Mandatory (Experience 2) – Must have strong backend engineering experience using Python (FastAPI / Django preferred) and building production-grade systems
• Mandatory (Experience 3) – Must have hands-on experience building LLM-based applications, including OpenAI / Gemini / similar models in real projects
• Mandatory (Experience 4) – Must have experience with RAG (Retrieval Augmented Generation) including chunking, embeddings, and retrieval pipelines
• Mandatory (Experience 5) – Must have experience designing end-to-end AI pipelines, including chaining, tool usage, structured outputs, and handling failure cases
• Mandatory (Experience 6) – Must have experience building agentic AI systems (multi-step workflows, tool orchestration like LangGraph / CrewAI or custom agents)
• Mandatory (Experience 7) – Must have strong coding and system design skills, not just prompt engineering or experimentation
• Mandatory (Experience 8) – Must have experience shipping AI features in production, not just POCs or research projects
• Mandatory (Experience 9) – Must have experience working with APIs, backend services, and integrations
• Mandatory (Experience 10) – Must have understanding of AI system reliability, including latency, cost optimization, fallback handling, and basic eval thinking
• Mandatory (Company) – Product companies / startups, preferably Series A to Series D
• Mandatory (Note) - Candidate's overall experience should not be more than 7 Yrs
• Mandatory (Tech Stack) – Strong in Python + AI/LLM ecosystem, experience with modern AI tooling and frameworks
• Mandatory (Exclusion) – Reject profiles that are only Prompt Engineers, Data Scientists, or Frontend Engineers without strong backend + system building experience
• Preferred (Skill) – Experience with fine-tuning (LoRA / QLoRA) or open-source model deployment (vLLM / Ollama)
• Preferred (Frontend) – Basic ability to build or contribute to frontend (React or similar)
• Highly Preferred (Education) – Candidates from Tier-1 institutes (IITs, BITS, NITs, IIITs, top global universities)

Job Title: AI Architecture Intern

Company: PGAGI Consultancy Pvt. Ltd.

Location: Remote

Employment Type: Internship

Position Overview

We're at the forefront of creating advanced AI systems, from fully autonomous agents that provide intelligent customer interaction to data analysis tools that offer insightful business solutions. We are seeking enthusiastic interns who are passionate about AI and ready to tackle real-world problems using the latest technologies.

Duration: 6 months

Key Responsibilities:

• AI System Architecture Design: Collaborate with the technical team to design robust, scalable, and high-performance AI system architectures aligned with client requirements.
• Client-Focused Solutions: Analyze and interpret client needs to ensure architectural solutions meet expectations while introducing innovation and efficiency.
• Methodology Development: Assist in the formulation and implementation of best practices, methodologies, and frameworks for sustainable AI system development.
• Technology Stack Selection: Support the evaluation and selection of appropriate tools, technologies, and frameworks tailored to project objectives and future scalability.
• Team Collaboration & Learning: Work alongside experienced AI professionals, contributing to projects while enhancing your knowledge through hands-on involvement.

Requirements:

• Strong understanding of AI concepts, machine learning algorithms, and data structures.
• Familiarity with AI development frameworks (e.g., TensorFlow, PyTorch, Keras).
• Proficiency in programming languages such as Python, Java, or C++.
• Demonstrated interest in system architecture, design thinking, and scalable solutions.
• Up-to-date knowledge of AI trends, tools, and technologies.
• Ability to work independently and collaboratively in a remote team environment

Perks:

- Hands-on experience with real AI projects.

- Mentoring from industry experts.

- A collaborative, innovative and flexible work environment

Compensation:

- Stipend: Base is INR 8000/- & can increase up to 20000/- depending upon performance matrix.

After completion of the internship period, there is a chance to get a full-time opportunity as an AI/ML engineer.

Preferred Experience:

• Prior experience in roles such as AI Solution Architect, ML Architect, Data Science Architect, or AI/ML intern.
• Exposure to AI-driven startups or fast-paced technology environments.
• Proven ability to operate in dynamic roles requiring agility, adaptability, and initiative.

About PGAGI:

We're at the forefront of creating advanced AI systems, from fully autonomous agents that provide intelligent customer interaction to data analysis tools that offer insightful business solutions. We are seeking enthusiastic interns who are passionate about AI and ready to tackle real-world problems using the latest technologies.

About the Role

We are at the forefront of building advanced AI systems — from fully autonomous agents that power intelligent customer interactions, to data analysis tools that deliver actionable business insights. This internship combines hands-on AI/ML engineering with robust backend development, giving you a complete picture of how production-grade AI systems are built, deployed, and scaled.

You will work across the full stack: designing and fine-tuning AI models on one end, and architecting the APIs, databases, and server-side infrastructure that bring those models to life on the other.

Key Responsibilities

AI / ML ENGINEERING

Design, experiment with, and fine-tune large language models (LLMs) and NLP pipelines for real-world use cases.

Develop and iterate on prompt engineering strategies to optimise model performance and output quality.

Integrate and deploy models using Hugging Face and OpenAI platforms; evaluate open-source alternatives.

Build deep learning workflows including training, evaluation, and continuous improvement loops.

Collaborate on data collection, preprocessing, and feature engineering for ML pipelines.

BACKEND ENGINEERING

Architect and develop scalable RESTful APIs and GraphQL endpoints using Node.js / FastAPI / Express.

Build and maintain full-stack features using Next.js (App Router), integrating server-side rendering, API routes, and React components.

Design and manage relational and NoSQL databases (PostgreSQL, MongoDB, or equivalent); write efficient queries and manage schema migrations.

Implement authentication, authorisation, and security best practices (JWT, OAuth 2.0, role-based access control).

Containerise services with Docker and contribute to CI/CD pipelines for reliable, automated deployments.

Integrate AI/ML model inference endpoints into backend services, handling async processing, queuing, and latency optimisation.

Write clean, well-tested, and well-documented backend code; participate actively in code reviews.

VERSION CONTROL & COLLABORATION

Use Git and GitHub for all version control workflows — branching strategies, pull requests, and code reviews.

Contribute to technical documentation, architecture decision records, and internal knowledge bases.

Duration & Compensation

Duration: 6 Months

Stipend: Base ₹8,000/month — up to ₹15,000/month based on performance

Post-Internship: Full-time opportunity as AI/ML Engineer (₹6–8 LPA) based on performance

Perks & Benefits

Hands-on experience shipping real AI products used by actual customers.

Mentorship from senior engineers and industry experts in AI/ML and backend development.

Exposure to the full development lifecycle — from model training to production deployment.

Collaborative, innovative, and flexible work environment.

Accelerated growth path with a clear route to a full-time engineering role.

How to Apply

Interested candidates are invited to submit their resume and complete the assignment using

the link : https://pgagi.in/jobs/28df1e98-f0c3-4d58-9509-d5b1a4ea9754

Shortlisted candidates will be contacted for an interview.

Selection Process

Initial Screening: We'll review your application for evidence of your skills, experience, and a strong foundation in AI.

Task Assignment: Candidates need to submit assignment which is already being attached in careers page , designed to assess your practical skills.

Performance Review: Our experts will evaluate your task submission, with excellence in this stage being crucial for further consideration.

Interview: Impressive task performers will be invited for an interview to discuss their potential contribution to our team.

Onboarding: Successful candidates will join our team, with exciting projects ahead

Requirements

MUST-HAVE SKILLS

Strong proficiency in Python for AI/ML development and scripting.

Solid understanding of JavaScript / TypeScript; experience with Node.js and Next.js (or a strong willingness to learn quickly).

Familiarity with REST API design principles and at least one backend framework (Express, FastAPI, Django, etc.).

Working knowledge of at least one database system (PostgreSQL, MySQL, MongoDB).

Experience with Git and GitHub version control workflows.

Exposure to AI/ML platforms such as Hugging Face and OpenAI.

Understanding of prompt engineering concepts and the model fine-tuning process.

GOOD TO HAVE

Hands-on experience with Next.js App Router, React Server Components, or similar modern full-stack frameworks.

Familiarity with Docker, basic DevOps concepts, or cloud platforms (AWS, GCP, or Azure).

Experience with message queues (Redis, RabbitMQ) or background task processing.

Knowledge of LLM orchestration tools such as LangChain or LlamaIndex.

SOFT SKILLS & MINDSET

Strong problem-solving instincts and a genuine curiosity about AI technology.

Ability to own tasks end-to-end and communicate progress clearly.

Comfortable working in a fast-moving environment where requirements evolve.

A growth mindset — eager to learn, receive feedback, and level up continuously.

TECH YOU'LL WORK WITH

Python

Next.js

Node.js

FastAPI

LLMs / NLP

PostgreSQL

React

Docker

HuggingFace

OpenAI API

GitHub

REST / GraphQL

Apply now to embark on a transformative career journey with PGAGI, where innovation and talent converge!

#artificialintelligence #Machinelearning #AI #AIML #LLM #FastAPI #NLP #openAI #AImodels #AIMLInternship #AIintern #Internship #aimlgraduate #Python

Job Title: AI/ML Engineer – Voice (2–3 Years)

Location: Bengaluru (On-site)

Employment Type: Full-time

About Impacto Digifin Technologies

Impacto Digifin Technologies enables enterprises to adopt digital transformation through intelligent, AI-powered solutions. Our platforms reduce manual work, improve accuracy, automate complex workflows, and ensure compliance—empowering organizations to operate with speed, clarity, and confidence.

We combine automation where it’s fastest with human oversight where it matters most. This hybrid approach ensures trust, reliability, and measurable efficiency across fintech and enterprise operations.

Role Overview

We are looking for an AI Engineer Voice with strong applied experience in machine learning, deep learning, NLP, GenAI, and full-stack voice AI systems.

This role requires someone who can design, build, deploy, and optimize end-to-end voice AI pipelines, including speech-to-text, text-to-speech, real-time streaming voice interactions, voice-enabled AI applications, and voice-to-LLM integrations.

You will work across core ML/DL systems, voice models, predictive analytics, banking-domain AI applications, and emerging AGI-aligned frameworks. The ideal candidate is an applied engineer with strong fundamentals, the ability to prototype quickly, and the maturity to contribute to R&D when needed.

This role is collaborative, cross-functional, and hands-on.

Key Responsibilities

Voice AI Engineering

• Build end-to-end voice AI systems, including STT, TTS, VAD, audio processing, and conversational voice pipelines.
• Implement real-time voice pipelines involving streaming interactions with LLMs and AI agents.
• Design and integrate voice calling workflows, bi-directional audio streaming, and voice-based user interactions.
• Develop voice-enabled applications, voice chat systems, and voice-to-AI integrations for enterprise workflows.
• Build and optimize audio preprocessing layers (noise reduction, segmentation, normalization)
• Implement voice understanding modules, speech intent extraction, and context tracking.

Machine Learning & Deep Learning

• Build, deploy, and optimize ML and DL models for prediction, classification, and automation use cases.
• Train and fine-tune neural networks for text, speech, and multimodal tasks.
• Build traditional ML systems where needed (statistical, rule-based, hybrid systems).
• Perform feature engineering, model evaluation, retraining, and continuous learning cycles.

NLP, LLMs & GenAI

• Implement NLP pipelines including tokenization, NER, intent, embeddings, and semantic classification.
• Work with LLM architectures for text + voice workflows
• Build GenAI-based workflows and integrate models into production systems.
• Implement RAG pipelines and agent-based systems for complex automation.

Fintech & Banking AI

• Work on AI-driven features related to banking, financial risk, compliance automation, fraud patterns, and customer intelligence.
• Understand fintech data structures and constraints while designing AI models.

Engineering, Deployment & Collaboration

• Deploy models on cloud or on-prem (AWS / Azure / GCP / internal infra).
• Build robust APIs and services for voice and ML-based functionalities.
• Collaborate with data engineers, backend developers, and business teams to deliver end-to-end AI solutions.
• Document systems and contribute to internal knowledge bases and R&D.

Security & Compliance

• Follow fundamental best practices for AI security, access control, and safe data handling.
• Awareness of financial compliance standards (plus, not mandatory).
• Follow internal guidelines on PII, audio data, and model privacy.

Primary Skills (Must-Have)

Core AI

• Machine Learning fundamentals
• Deep Learning architectures
• NLP pipelines and transformers
• LLM usage and integration
• GenAI development
• Voice AI (STT, TTS, VAD, real-time pipelines)
• Audio processing fundamentals
• Model building, tuning, and retraining
• RAG systems
• AI Agents (orchestration, multi-step reasoning)

Voice Engineering

• End-to-end voice application development
• Voice calling & telephony integration (framework-agnostic)
• Realtime STT ↔ LLM ↔ TTS interactive flows
• Voice chat system development
• Voice-to-AI model integration for automation

Fintech/Banking Awareness

• High-level understanding of fintech and banking AI use cases
• Data patterns in core banking analytics (advantageous)

Programming & Engineering

• Python (strong competency)
• Cloud deployment understanding (AWS/Azure/GCP)
• API development
• Data processing & pipeline creation

Secondary Skills (Good to Have)

• MLOps & CI/CD for ML systems
• Vector databases
• Prompt engineering
• Model monitoring & evaluation frameworks
• Microservices experience
• Basic UI integration understanding for voice/chat
• Research reading & benchmarking ability

Qualifications

• 2–3 years of practical experience in AI/ML/DL engineering.
• Bachelor’s/Master’s degree in CS, AI, Data Science, or related fields.
• Proven hands-on experience building ML/DL/voice pipelines.
• Experience in fintech or data-intensive domains preferred.

Soft Skills

• Clear communication and requirement understanding
• Curiosity and research mindset
• Self-driven problem solving
• Ability to collaborate cross-functionally
• Strong ownership and delivery discipline
• Ability to explain complex AI concepts simply

Company Description

Recruiting Bond International is a next-generation Talent Intelligence, Executive Search, and Human Capital Advisory firm helping start-ups, enterprises, GCCs, and VC/PE-backed companies build high-impact global teams. It is a global leader in Recruitment Process Outsourcing (RPO), executive search, and workforce consulting, specializing in building transformative talent strategies.

From high-growth startups to Fortune 500 companies, Recruiting Bond partners with organizations across 50+ industries and 140+ countries to deliver fast, scalable, and inclusive hiring solutions. The company supports businesses in scaling teams, fostering innovation, and creating talent-first strategies to achieve their goals.

With deep expertise across Technology, FinTech, Healthcare, Real Estate, and Energy, Recruiting Bond is dedicated to building careers, companies, and futures by connecting world-class talent with high-impact opportunities globally.

About the Role

Our client is hiring a Backend Engineer (India-based, Remote) to design, build, and scale the core memory infrastructure powering production-grade AI agents.

This role is intended for an experienced engineer with 7–10 years of backend engineering experience, who has deeply internalized AI-native engineering practices and actively builds using tools such as Claude Code, Codex, Cursor, Windsurf, or comparable AI development tools as a core part of their workflow.

The hiring process is intentionally non-traditional and skill-first. There is no evaluation based on IIT pedigree, LeetCode performance, or conventional resume filters. Instead, the only evaluation criterion is: how you build with AI in real-world scenarios.

Candidates are expected to submit prompt logs or transcripts from Claude Code, Codex, Cursor, or Windsurf demonstrating a feature or product they are proud of.

What You'll Own

• Build and scale backend systems powering the memory infrastructure of the product
• Own and deliver features end-to-end, integrating AI coding tools into the core development workflow
• Design, manage, and optimize database, storage, and retrieval systems for persistent memory
• Collaborate closely on system architecture, scalability, performance, and reliability engineering
• Contribute directly to product roadmap decisions based on real customer usage and production insights

Requirements

Must-Have

• 7–10 years of backend engineering experience
• Demonstrated ability to build with AI coding tools (Claude Code, Codex, Cursor, Windsurf, or comparable)
• Ability and willingness to submit prompt log transcripts from a feature or product you are proud of
• Strong Python fundamentals
• Strong PostgreSQL or comparable relational database fundamentals
• Comfort owning systems end-to-end in production
• Based in India, remote work from anywhere in the country

Nice-to-Have

• Prior AI infrastructure or developer tools product experience
• FastAPI fluency
• Open-source contributions in AI, memory, vector databases, or developer tools
• Prior experience in memory systems, RAG pipelines, or vector database engineering
• Public technical writing or conference talks on AI-native engineering practices

About Techjays

At Techjays, we build production-grade AI platforms for global clients. We operate at the intersection of backend engineering, distributed systems, and applied AI — delivering secure, scalable, and enterprise-ready intelligent systems. Our team has built and scaled products at Google, Akamai, NetApp, ADP, Cognizant, and Capgemini.

About the Role

This is not a feature-delivery role. We are looking for an AI Lead who can architect, own, and scale intelligent backend systems end-to-end. You will drive both technical direction and execution — working across LLM integrations, RAG pipelines, agentic AI workflows, and cloud-native backend systems for global clients.

What You'll Do

• Architect and scale backend systems powering AI-driven applications
• Design and implement RAG pipelines, AI agents, and LLM integrations
• Own systems end-to-end — from architecture to deployment and scaling
• Integrate and optimize LLMs (Claude, GPT, Gemini) for real-world production use cases
• Build high-performance distributed systems with observability and cost efficiency
• Lead backend and AI initiatives with strong technical ownership
• Mentor engineers and raise the technical bar across teams
• Collaborate with product and AI teams to deliver AI-native solutions

What We're Looking For

• 6–10 years of strong backend engineering experience
• Hands-on expertise in Python (FastAPI / Django / Flask)
• Deep understanding of Generative AI and LLM-based systems
• Strong experience with RAG pipelines and Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate)
• Solid knowledge of Agentic AI — building autonomous agents and multi-agent workflows
• Proficiency in AWS or GCP in production environments
• Experience with distributed systems, microservices, and system design
• Strong grasp of Data Structures, Algorithms, and Design Patterns
• Familiarity with WebSockets, Git, Linux/Unix, and CI/CD

Nice to Have

• Experience with Anthropic Claude API and Claude Code
• Familiarity with real-time data systems or streaming (Kafka, etc.)
• MLOps and AI system lifecycle experience
• Optimizing AI systems for latency, cost, and scalability

Who You Are

• You think in systems, not just features
• You take full ownership of what you build
• You are comfortable navigating fast-moving, ambiguous environments
• You stay updated with the latest in Generative AI and backend technologies
• Strong communicator who can collaborate across teams and global clients

What We Offer

• Competitive compensation (Best in Industry)
• Work on production-grade AI systems used by global clients
• Exposure to cutting-edge AI tools and frameworks
• A culture that values clarity, integrity, and continuous growth

About the Role

At Techjays, we build production-grade AI systems for global clients. We are looking for a Solution Architect who can bridge the gap between client needs and technical delivery — someone who can walk into a client room, understand their business challenges, and walk out with a compelling, technically sound AI solution.

This role sits at the intersection of pre-sales, solutioning, and delivery governance.

What You'll Do

• Own end-to-end solutioning from client discovery to architecture design
• Partner with pre-sales teams on RFPs, proposals, and client presentations
• Define architectures for LLM integrations, RAG pipelines, and agentic workflows
• Conduct architecture reviews and technical assessments for ongoing projects
• Act as a trusted technical advisor to enterprise clients during pre-sales

Key Skills

• Python, REST APIs, Microservices, Distributed Systems
• AWS / Azure / GCP, Docker, Kubernetes, CI/CD
• LLM Integrations, RAG Pipelines, AI Agents, Vector Databases
• Enterprise data architecture and integration patterns
• Strong client communication and presentation skills

Who You Are

• Client-first mindset — listens, understands, and translates business pain into technical clarity
• Strong communicator comfortable with C-level stakeholders
• High ownership — accountable for every solution you sign off on
• Collaborative across sales, delivery, and engineering

What We Offer

• Flexible work environment
• Paid holidays & flexible time off
• Medical insurance (Self & Family up to ₹4 Lakhs)
• Exposure to global clients and high-impact pre-sales engagements
• A culture of clarity, integrity, and continuous growth

About Techjays

At Techjays, we build production-grade AI platforms for global clients. We operate at the intersection of backend engineering, distributed systems, and applied AI — delivering secure, scalable, and enterprise-ready intelligent systems. Our team has built and scaled products at Google, Akamai, NetApp, ADP, Cognizant, and Capgemini.

About the Role

This is not a feature-delivery role. We are looking for an AI Lead who can architect, own, and scale intelligent backend systems end-to-end. You will drive both technical direction and execution — working across LLM integrations, RAG pipelines, agentic AI workflows, and cloud-native backend systems for global clients.

What You'll Do

• Architect and scale backend systems powering AI-driven applications
• Design and implement RAG pipelines, AI agents, and LLM integrations
• Own systems end-to-end — from architecture to deployment and scaling
• Integrate and optimize LLMs (Claude, GPT, Gemini) for real-world production use cases
• Build high-performance distributed systems with observability and cost efficiency
• Lead backend and AI initiatives with strong technical ownership
• Mentor engineers and raise the technical bar across teams
• Collaborate with product and AI teams to deliver AI-native solutions

What We're Looking For

• 6–10 years of strong backend engineering experience
• Hands-on expertise in Python (FastAPI / Django / Flask)
• Deep understanding of Generative AI and LLM-based systems
• Strong experience with RAG pipelines and Vector Databases (Pinecone, FAISS, ChromaDB, Weaviate)
• Solid knowledge of Agentic AI — building autonomous agents and multi-agent workflows
• Proficiency in AWS or GCP in production environments
• Experience with distributed systems, microservices, and system design
• Strong grasp of Data Structures, Algorithms, and Design Patterns
• Familiarity with WebSockets, Git, Linux/Unix, and CI/CD

Nice to Have

• Experience with Anthropic Claude API and Claude Code
• Familiarity with real-time data systems or streaming (Kafka, etc.)
• MLOps and AI system lifecycle experience
• Optimizing AI systems for latency, cost, and scalability

Who You Are

• You think in systems, not just features
• You take full ownership of what you build
• You are comfortable navigating fast-moving, ambiguous environments
• You stay updated with the latest in Generative AI and backend technologies
• Strong communicator who can collaborate across teams and global clients

What We Offer

• Competitive compensation (Best in Industry)
• Work on production-grade AI systems used by global clients
• Exposure to cutting-edge AI tools and frameworks
• A culture that values clarity, integrity, and continuous growth