
AI Engineer
2 days ago
Job Description: AI Engineer (0–2 Years Experience)
About the Role
We are seeking a motivated AI Engineer (entry-level to early career) with a strong foundation in AI/ML concepts and hands-on experience in building AI agents using modern frameworks, LLMs, and automation tools. You will work closely with senior engineers, product managers, and researchers to design, develop, and deploy intelligent agent-based solutions that solve real-world business problems.
Key Responsibilities
Design, develop, and deploy AI agents capable of reasoning, planning, and interacting with APIs, knowledge bases, and external systems.
Leverage Large Language Models (LLMs) (e.g., GPT, Claude, LLaMA, Mistral) and fine-tune them for specific tasks.
Build pipelines for data ingestion, preprocessing, and embedding generation to enable contextual and retrieval-augmented intelligence.
Integrate AI agents with external tools, APIs, and enterprise systems (databases, CRM, cloud platforms, etc.).
Collaborate with cross-functional teams to translate business requirements into AI-powered workflows.
Stay up-to-date with emerging AI frameworks (LangChain, LlamaIndex, Haystack, Semantic Kernel, CrewAI, AutoGen, etc.) and orchestration platforms.
Support the evaluation, testing, and monitoring of AI models to ensure reliability, accuracy, and ethical usage.
Contribute to proof-of-concepts (POCs) and help scale them into production-ready systems.
Required Qualifications
0–2 years of experience in AI/ML, NLP based software engineering.
Strong programming skills in Python (experience with libraries such as PyTorch, TensorFlow, Hugging Face, LangChain, etc.).
Understanding of LLM fundamentals, prompt engineering, embeddings, and fine-tuning.
Experience with REST APIs, vector databases (e.g., Pinecone, Weaviate, Milvus, FAISS), and any one cloud platforms (AWS, Azure, GCP).
Knowledge of agent frameworks (LangChain Agents, AutoGPT, CrewAI, etc.) and orchestration tools.
Solid understanding of data structures, algorithms, and software engineering best practices.
Familiarity with Git, CI/CD, Docker, and basic MLOps concepts.
Strong problem-solving skills, eagerness to learn, and ability to work in collaborative environments.
Preferred / Nice to Have
Exposure to retrieval-augmented generation (RAG) pipelines.
Hands-on experience with Databricks, Azure ML, or Hugging Face Hub.
Familiarity with multi-agent architectures or autonomous AI systems.
Understanding of responsible AI practices (bias, fairness, explainability).
Contributions to open-source AI projects or personal AI side projects.
What We Offer
Opportunity to work on cutting-edge AI agent solutions with real business impact.
Mentorship from experienced AI and software engineers.
Fast-paced, innovation-driven environment with room for growth.
Access to the latest AI tools, frameworks, and research.
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