AI Engineer at iDreamCareercom · Delhi · 1 - 3 years · ₹10L - ₹18L / yr · Profitable · Posted 5 May 2026
What we are looking for:
We are looking for a motivated AI Developer with 1–3 years of experience to join our team and build cutting-edge applications powered by Large Language Models (LLMs). You will work on designing, developing, and optimizing intelligent systems using modern AI frameworks and tools.
Responsibilities:
- Design and develop applications leveraging Large Language Models (LLMs)
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines
- Work with frameworks like LangChain, LangGraph, or similar LLM orchestration tools
- Integrate and manage vector databases (e.g., Pinecone, Weaviate, Qdrant, FAISS)
- Implement prompt engineering strategies and improve model responses
- Develop scalable and efficient AI system architectures
- Monitor, debug, and optimize LLM applications using observability tools (e.g., Langfuse or similar)
- Collaborate with backend and product teams to integrate AI features into production systems
- Stay updated with the latest advancements in AI/LLM ecosystem
Skills:
- 1–3 years of hands-on experience in AI/ML or backend development with AI exposure
- Strong understanding of LLMs and generative AI concepts
- Experience with LangChain, LangGraph, or similar frameworks
- Practical experience with RAG architectures and pipelines
- Hands-on experience with vector databases (e.g., Pinecone, Qdrant, Weaviate, FAISS)
- Familiarity with observability tools like Langfuse, Helicone, or similar
- Proficiency in Python (preferred) or Node.js
- Experience working with APIs (OpenAI, Anthropic, etc.)
- Understanding of embeddings, chunking, and retrieval strategies
- Good problem-solving and debugging skills
Experience:
- 1-3 years of experience in AI application development
Remuneration: Industry Standard basis experience
Shubham Vishwakarma
Full Stack Developer - Averlon
About iDreamCareercom
About
iDreamCareer is India’s most trusted Career Guidance company, working with leading pvt schools, CSR & govt and career counsellors, since 2012. We are the Technical Partner to CBSE for Career Guidance, and were the first Career Guidance company to feature on Shark Tank India.
BlueSpring is our private school program, while for govt school students, we implement PathShila, in partnership with CSR & other social impact bodies like the UN.
Both BlueSpring and PathShila have three foundational pillars - Process, People & Platform (PPP).
Process - refined over the last 13 years and is designed to be holistic and customised for each school / partner.
People - we manage iDC Council: India’s largest community of 550+ active certified career counselors. Today, our certification is accredited by Boston University Wheelock College of Education & Human Development.
Platform - iDC ONE is India’s most comprehensive Career Guidance tech platform, designed for students, counsellors & school management.
This PPP approach has enabled us to achieve the highest counseling efficacy in the Career Guidance ecosystem. And this is how we deliver a structured, unbiased, informed & empathetic career counselling for students.
At iDC, we do what we do so that ultimately, we can build a world where every child gets to have a joyful career & a meaningful life.
Company video
Company social profiles
Similar jobs (10)
Support with design and build to prove out agentic AI solution flow by working with other data
scientists and engineers to build, train Large Language Model (LLM) architectures, RAG
systems, and autonomous agentic workflows
Key qualifications:
>> AI solution design & Development: Design Agentic AI solutions using RAG (Retrieval-
Augmented Generation) and orchestration frameworks like LangGraph or LangChain.
>> Model Fine-Tuning: Solid understanding and experience with Pre-train, fine-tune, and
optimize open-source like BERT, LLama, and other proprietary foundation models for domain-
specific tasks
>> Solid Stats and ML foundations and (vibe) coding skills with Python, PySpark
>> Implement validation frameworks and tracing practices (using tools like Arize) to monitor
agent behavior, guard against model drift, and ensure compliance
>> Collaborate with Engineering to deploy models securely on cloud and on-prem ecosystems
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Position Overview
We are seeking a highly skilled and experienced Senior AI/ML Developer to lead the development and integration of advanced AI solutions within our product ecosystem. This role involves close collaboration with cross-functional teams including product managers, data scientists, and engineers to build AI models that solve real-world integration challenges. The ideal candidate will have a strong foundation in machine learning, deep learning, and software development, along with hands-on experience deploying AI models in production environments.
Bachelor’s degree in computer science, Data Science, Mathematics, Engineering, or a related field.
✓
8+ years of experience in designing and implementing AI/ML solutions.
✓
Demonstrated ability to integrate AI models into production software.
✓
Excellent analytical thinking, communication, and problem-solving abilities.
✓
Ability to work autonomously as well as in a collaborative team setup.
Skills Required
✓
Dataset Development: Strong track record of building datasets for training and/or evaluating machine learning models.
✓
LLM and NLP Experience: Hands-on experience working with LLMs, RAG architecture, Natural Language Processing (NLP), or applying Machine Learning to solve real-world problems.
✓
Experience with LLM fine-tuning, prompt engineering, vector databases (e.g., Pinecone, FAISS) is highly desirable.
✓
Test Harness Automation for LLM Agents
✓
Familiarity with agent frameworks (e.g., Semantic Kernel, AutoGen, Lang Chain, etc.).
✓
Proficiency in Python and libraries like Pandas, NumPy, Scikit-learn, etc. containerization (Docker), and API frameworks (Flask, Fast API).
✓
Integration Knowledge: API development, data transformation, system integration
✓
Soft Skills: Communication, teamwork, adaptability, critical thinking
Job Description:
We are looking for a hands-on AI Engineer with experience in Generative AI and Agentic AI to build and deploy production-ready AI solutions.
Key Responsibilities:
- Develop and deploy GenAI and Agentic AI applications.
- Build RAG pipelines, LLM workflows, and AI agents.
- Develop solutions using Python, LangChain, LangGraph, LlamaIndex, or similar frameworks.
- Implement tool calling, context retrieval, and LLM orchestration.
- Integrate AI solutions with APIs and cloud platforms.
- Work with AWS/Azure/GCP, Docker, and CI/CD.
Required Skills:
- Strong Python programming skills.
- 3+ years of GenAI/Agentic AI experience.
- RAG and LLM orchestration.
- LangChain / LangGraph / LlamaIndex / AutoGen / CrewAI / Semantic Kernel.
- MCP and A2A knowledge.
- Cloud, APIs, Docker, and CI/CD experience.
Preferred Experience:
Hands-on experience building and deploying production-ready AI solutions.
Role: AI Developer
Experience: 3–4 Years
Employment Type: Full-Time
Location: Goregaon, Mumbai
About the Role
We are looking for an experienced AI Developer with 3–4 years of software development experience and strong hands-on exposure to Generative AI, AI Agents, Copilots, and AI-powered application development.
The candidate will be responsible for building production-ready AI solutions, developing agentic workflows, modernizing legacy applications, and integrating LLM capabilities into enterprise applications.
Key Responsibilities
- Design, develop, and deploy AI Agents and agentic workflows for enterprise use cases.
- Build AI Copilots and LLM-powered applications using modern AI frameworks and APIs.
- Develop RAG-based applications using embeddings, vector databases, and enterprise data.
- Work on legacy application migration and modernization, leveraging AI-assisted development and code transformation techniques.
- Analyze legacy codebases and design strategies for AI-driven migration, refactoring, and modernization.
- Integrate LLMs with enterprise applications, APIs, databases, and third-party systems.
- Implement tool calling, function calling, multi-agent workflows, and workflow automation.
- Perform prompt engineering, context optimization, model evaluation, and AI application testing.
- Take ownership of AI solutions from POC and prototyping through production deployment.
- Collaborate with product managers, architects, and engineering teams to convert business requirements into scalable AI solutions.
- Stay updated with emerging technologies in Generative AI, Agentic AI, LLMs, and AI-assisted software development.
Required Skills
- 3–4 years of professional software development experience.
- Strong proficiency in Python and/or JavaScript/TypeScript.
- Hands-on experience developing Generative AI / LLM-based applications.
- Strong understanding of AI Agents, RAG, Prompt Engineering, LLM APIs, and embeddings.
- Experience with frameworks such as LangChain, LangGraph, Semantic Kernel, AutoGen, or equivalent.
- Experience working with REST APIs, databases, Git, and cloud environments.
- Hands-on experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, or equivalent.
- Good understanding of software architecture, debugging, testing, and deployment practices.
Good to Have
- Experience with Microsoft Copilot / Copilot Studio.
- Experience working with Claude, OpenAI, Gemini, Azure OpenAI, or open-source LLMs.
- Experience in legacy application migration, modernization, or code conversion.
- Knowledge of Azure AI / AWS / Google Cloud AI services.
- Experience with MCP, multi-agent systems, tool calling, and AI orchestration.
- Experience building enterprise-grade AI solutions with focus on security, scalability, and performance.
We are seeking Generative AI Developers with strong Python programming and AI/ML expertise to build, deploy, and optimize LLM-powered applications. The role involves developing RAG solutions, AI agents, and enterprise GenAI applications while collaborating with cross-functional teams.
Key Responsibilities
- Develop and enhance Generative AI applications using LLMs and AI frameworks.
- Build and optimize RAG pipelines, vector search, and AI-powered workflows.
- Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA.
- Develop REST APIs and integrate AI capabilities into enterprise applications.
- Deploy, monitor, and maintain AI solutions in cloud and containerized environments.
- Ensure code quality through testing, debugging, documentation, and code reviews.
- Follow Responsible AI, security, and data governance practices.
Required Technical Skills
- Strong proficiency in Python, OOP, APIs, debugging, and software development best practices.
- Good understanding of Data Structures & Algorithms, complexity analysis, and problem-solving.
- Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings.
- Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks.
- Knowledge of vector databases, semantic/hybrid search, and retrieval architectures.
- Experience with PyTorch, TensorFlow, or Keras.
- Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP).
- Understanding of AI governance, data privacy, and Responsible AI principles.
Preferred Skills
- Experience with Agentic AI frameworks (CrewAI, AutoGen, Semantic Kernel).
- Exposure to Azure AI Foundry, Databricks, or enterprise AI platforms.
- Knowledge of multimodal AI applications.
Qualifications
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.
- 5 years of software development experience, including AI/ML or Generative AI projects.
- Experience building and deploying production-grade AI solutions.
Assessment Focus Areas
Candidates will be evaluated on:
- Python coding and problem-solving
- Data Structures & Algorithms
- LLMs, RAG, and Agentic AI concepts
- API development and system design
- Cloud deployment and AI solution architecture
AI Engineer
LLMs, Agents & AI Services
📍 Mumbai (On-site) | Full-time | 2-4 years
About the Role:
Unico Connect is an AI-first technology partner that builds custom mobile, web, and AI products for clients across multiple geographies.
AI is core to how we design, deliver, and scale software for our customers.
We are hiring an AI Engineer for a dedicated client engagement building a complex production AI platform, working on the AI capabilities and agentic features at the core of the product.
The mandatory requirement for this role is at least one AI feature personally shipped to production for real users, with operational ownership.
The role suits someone who thinks quickly on solutioning, can take an ambiguous problem to a working prototype in days, and has the discipline to carry it through to production with predictable economics.
You will work alongside the Senior AI Engineer and the wider pod, with ownership of parts of the AI surface area of the product.
Responsibilities:
Solutioning and POCs
Translate ambiguous customer problems into working POCs at speed.
Pick the right model, framework, and architecture, and demonstrate value early before scaling investment.
LLM Application Development
Build AI features and services using LLM APIs from OpenAI, Anthropic, Google, and self-hosted open-weight models (Llama, Qwen, Mistral).
Choose the right model per use case based on cost, latency, capability, and context-window trade-offs.
Agentic System Design
Design and implement agentic workflows using LangGraph, CrewAI, AutoGen, LlamaIndex Agents, or custom orchestration.
Cover tool use, planning, memory, and multi-step reasoning appropriate to the problem.
API and Service Development
Build production AI services and APIs using Python and FastAPI.
Handle streaming responses, async processing, structured outputs, retries, and graceful degradation when models or tools fail.
Retrieval and Tool Integration
Implement RAG pipelines with vector databases (Pinecone, Weaviate, Qdrant, pgvector, Chroma), embeddings, chunking strategies, hybrid search, and reranking.
Integrate external tools, internal APIs, and document sources through tool-calling and MCP-style patterns.
Cost Analysis and Unit Economics
Model the per-request and per-user cost of every AI feature before it ships.
Track token usage, prompt caching, batching, and model-routing strategies.
Drive measurable improvements in unit economics.
Production Hardening
Add observability and tracing (LangSmith, Langfuse, OpenTelemetry), guardrails, content safety checks, prompt injection defences, and fallback behaviour.
Prompt Engineering and Evaluation
Design, test, and iterate prompts with measured outcomes.
Build evaluation harnesses for accuracy, hallucination, latency, and cost.
Run benchmarks across models and prompt variants before locking in a design.
Requirements:
AI Feature Shipped to Production (Mandatory)
Must have personally built and shipped at least one AI feature that runs in production for real users, with operational ownership.
POCs, internal demos, and one-off scripts do not qualify.
2 to 4 Years of Professional Software or AI Engineering Experience
With at least one production AI feature owned end to end.
Strong Python Proficiency and API Development with FastAPI
Comfort with type hints, async, packaging, testing, streaming responses, and authentication.
Production-grade Python, not notebook-only code.
Hands-on Depth Across the LLM and Agent Stack
Working experience with at least two of OpenAI, Anthropic Claude, Google Gemini, or self-hosted open-weight models (vLLM, Ollama, Together, Replicate).
Working familiarity with at least one agent framework (LangGraph, CrewAI, AutoGen, LlamaIndex Agents) or hand-rolled equivalent.
Working knowledge of RAG, embeddings, and vector databases (Pinecone, Weaviate, Qdrant, pgvector, Chroma).
Solutioning Speed and POC Velocity
Demonstrated ability to move from a fuzzy problem to a working prototype in days.
Strong instinct for what to build first, what to defer, and what to throw away.
Cost Discipline for Production AI
Ability to calculate, monitor, and optimise the cost of LLM APIs, tokens, embeddings, vector store usage, and infrastructure.
Treats unit economics as a first-class concern.
AWS Familiarity
Working knowledge of EC2, S3, IAM, and at least one of Bedrock, SageMaker, or equivalent.
Comfortable in a Fast-Moving Environment
Self-directed, comfortable with ambiguity, takes ownership without being asked, and ships under shifting priorities.
Strong Written and Spoken English Communication
Able to explain trade-offs to non-AI engineers, designers, product managers, and clients in plain language.
Nice to Have
- fine-tuning or LoRA, QLoRA, PEFT exposure
- MCP server authoring
- eval framework experience (LangSmith, Promptfoo, Ragas, DeepEval)
- open-source AI contributions
- multi-modal models (vision, audio)
The recruiter has not been active on this job recently. You may apply but please expect a delayed response.
Location: Jaipur (Work From Office)
Employment Type: Full-Time
We're looking for a GenAI Engineer (LLM Engineer) to build scalable AI-powered SaaS applications using Large Language Models (LLMs). You'll develop intelligent AI workflows, integrate LLMs into production systems, and build secure, high-performance AI solutions.
Key Responsibilities
- Integrate LLM APIs (OpenAI, Claude, Hugging Face) into production applications.
- Design and optimize RAG pipelines and prompt engineering workflows.
- Build and manage Vector Databases (Pinecone, Weaviate, pgvector).
- Optimize AI performance, latency, and operational cost.
- Ensure secure, scalable AI architecture.
- Collaborate with Product and Engineering teams to deliver AI-powered features.
Requirements
- 3+ years of backend development using Python, Go, or Node.js.
- Hands-on experience with LLMs, LangChain or LlamaIndex.
- Strong understanding of RAG, Prompt Engineering, and Vector Databases.
- Experience with AWS, GCP, or Azure.
- Knowledge of APIs, Microservices, and AI application development.
Preferred: Experience in SaaS/FinTech, LLMOps, or Model Fine-tuning.
Education: B.Tech, BCA, or equivalent technical qualification.
Apply Now
Application Form: https://zfrmz.com/pAKb2ynfomIsuNwRfRbV?utm_source=cutshort
Strong AI Engineer / Machine Learning Engineer profiles.
2
Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.
3
Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.
4
Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.
5
Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.
6
Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.
7
Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.
8
Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.
9
Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.
10
Mandatory (Age) - Candidate's Age should be below 28 Years
11
Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.
12
Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..
13
Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.
14
Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies
15
Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.
Strong AI/ML Engineer Profile
Mandatory (Experience) : Must have 3+ years of experience in software engineering with atleast 1+ years in GenAI application development and production deployment
Mandatory (GenAI Application Development): Must have proven experience building GenAI applications covering RAG pipelines, multi-agent systems, Text2SQL, and fine-tuning
Mandatory (Production GenAI Deployment): Must have expertise deploying production-grade GenAI applications including model evaluation, optimisation, and ownership of full production rollouts
Mandatory (ML & Data Science Tooling): Must have strong hands-on experience with core ML and data science tools including pandas, scikit-learn, and PyTorch
Mandatory (Cloud ML Infrastructure): Must have experience building and deploying production-grade ML workloads on at least one of AWS, Azure, or GCP
Mandatory (Communication): Must have strong English communication skills with the ability to work across time zones and collaborate cross-functionally with product, engineering, and business stakeholders
Mandatory (Note 1) : Role is Hybrid, WFH flexibility as well upto 6 days a month
Mandatory (Note 2) : CTC is inclusive of 10% variable
Mandatory (Note 3): Candidates should be available to join within May 31st or June first week max
Strong AI Engineer / Machine Learning Engineer profiles.
2
Mandatory (Experience 1) – Must have minimum 3+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI solutions.
3
Mandatory (Experience 2) – Must have strong hands-on experience in Python programming, SQL, data analysis, feature engineering, model development, and production-grade ML applications.
4
Mandatory (Experience 3) – Must have experience working with Machine Learning and Deep Learning frameworks such as PyTorch, TensorFlow, Keras, Scikit-learn, or equivalent.
5
Mandatory (Experience 4) – Must have hands-on experience working on NLP, embeddings, semantic search, text classification, document understanding, recommendation systems, or similar AI/ML use cases.
6
Mandatory (Experience 5) – Must have experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar foundation models.
7
Mandatory (Experience 6) – Must have hands-on experience building or implementing RAG (Retrieval Augmented Generation) systems, vector search, knowledge retrieval, embeddings, chunking, indexing, or semantic retrieval solutions.
8
Mandatory (Experience 7) – Must have experience working with Git, CI/CD practices, production environments, and scalable AI/ML systems.
9
Mandatory (CTC) – The CTC breakup offered will be 75% fixed + 25% variable, as per company policy.
10
Mandatory (Age) - Candidate's Age should be below 30 Years
11
Preferred (Experience 1) – Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, or MLOps/LLMOps frameworks.
12
Preferred (Experience 2) – Experience working with Vector Databases, Spark, PySpark, distributed ML pipelines, large-scale data processing, or real-time ML systems..
13
Preferred (Experience 3) – Familiarity with Docker, Kubernetes, Azure, AWS, GCP, cloud-native AI deployments, and scalable ML architecture.
14
Preferred (Company) – Candidates from AI-first startups, Fintech, Banking, Lending, Fraud Analytics, Risk Analytics, Product Companies, SaaS organizations, or data-driven technology companies
15
Mandatory ( Pedigree) - B.TECH / M.TECH from Tier 1 Colleges (IIT's, NIT's, BITS) are Considered.
Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon