Nectar is an AI-first product company building intelligent platforms that transform how enterprises leverage AI, automation, and connected technologies. Our products combine Generative AI, Agentic AI, IoT, and cloud-native technologies to deliver intelligent, scalable, and secure experiences for customers worldwide.
At Nectar, we continuously innovate and enhance our core product platform, enabling organizations to unlock actionable insights, automate operations, and make data-driven decisions in real time.
As an AI Engineer at Nectar, you will contribute to the development and enhancement of AI capabilities within our core product platform. You will work on building production-ready AI features powered by Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and intelligent automation.
You will collaborate closely with product, engineering, and design teams to build innovative AI experiences that directly impact our customers. This role offers an opportunity to work on cutting-edge AI technologies while contributing to the evolution of a fast-growing product.
- Develop and integrate AI features into Nectar's core product platform.
- Build and enhance Retrieval-Augmented Generation (RAG) pipelines and enterprise knowledge systems.
- Develop intelligent agents and automation workflows to improve product capabilities.
- Collaborate with Product, UI/UX, Backend, and IoT teams to deliver AI-powered experiences.
- Work with IoT-generated data to enable predictive insights and intelligent automation.
- Optimize AI applications for performance, reliability, scalability, and cost efficiency.
- Build reusable AI components and services that can be leveraged across the platform.
- Monitor and improve production AI systems based on customer feedback and usage patterns.
- Participate in technical discussions, code reviews, and architecture improvements.
- Follow responsible AI, security, and data governance best practices throughout the development lifecycle.
- Stay updated with the latest advancements in Generative AI and evaluate their applicability to the product.
RequirementsRequired Experience
- 1–3 years of hands-on experience in software development, AI/ML, or Generative AI applications.
- Strong programming skills in Python and experience building backend applications or APIs.
- Experience working with Large Language Models (LLMs) and Generative AI frameworks.
- Hands-on experience with RAG pipelines, embeddings, and vector databases is preferred.
- Familiarity with frameworks such as LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks.
- Understanding of REST APIs, microservices, and modern software development practices.
- Experience working with databases such as PostgreSQL, MongoDB, or Redis.
- Basic understanding of cloud platforms such as AWS, Azure, or GCP.
- Familiarity with Docker, Git, and CI/CD concepts.
- Strong problem-solving skills and a passion for building AI-powered products.
- Good communication and collaboration skills with the ability to work in cross-functional teams.
- Programming Languages: Python, SQL, JavaScript
- Generative AI: OpenAI, Anthropic, Gemini, Llama, Prompt Engineering
- AI Frameworks: LangChain, LangGraph, LlamaIndex, CrewAI
- RAG & Search: Embeddings, Semantic Search, Vector Databases
- Vector Databases: Pinecone, ChromaDB, FAISS, Weaviate
- Backend Development: FastAPI, Flask, REST APIs
- Cloud Platforms: AWS, Azure, or GCP
- Databases: PostgreSQL, MongoDB, Redis
- DevOps & Deployment: Docker, Git, CI/CD
- Data Processing: Pandas, NumPy, Real-time Data Processing
- Bachelor's degree in Computer Science, Artificial Intelligence, Engineering, or a related field.
- Relevant certifications or hands-on project experience in AI/ML or Generative AI will be an added advantage.
- Experience building AI-powered applications or personal/open-source AI projects.
- Exposure to IoT platforms, telemetry systems, or real-time data processing.
- Familiarity with MLOps concepts and model deployment workflows.
- Contributions to open-source projects, technical blogs, or AI communities are a plus.
Benefits
- Build AI features that directly power and enhance Nectar's core product platform.
- Work on cutting-edge technologies including Generative AI, Agentic AI, and IoT.
- Gain end-to-end ownership of features from development to deployment and continuous improvement.
- Collaborate with a passionate and innovative product engineering team.
- Continuous learning opportunities, certifications, and career growth in AI and product engineering.
- Work in a fast-paced environment where your contributions have visible and lasting impact.
Skills Required
- 1-3 years of hands-on experience in software development, AI/ML, or Generative AI applications
- Strong programming skills in Python
- Experience building backend applications or APIs
- Experience working with Large Language Models and Generative AI frameworks
- Experience with RAG pipelines, embeddings, and vector databases
- Familiarity with LangChain, LangGraph, LlamaIndex, or similar AI orchestration frameworks
- Understanding of REST APIs, microservices, and modern software development practices
- Experience with PostgreSQL, MongoDB, or Redis
- Basic understanding of AWS, Azure, or GCP
- Familiarity with Docker, Git, and CI/CD concepts
- Strong problem-solving skills
- Good communication and cross-functional collaboration skills
- Bachelor's degree in Computer Science, Artificial Intelligence, Engineering, or a related field
- Relevant AI/ML or Generative AI certifications or hands-on project experience
- Experience building AI-powered applications or personal/open-source AI projects
- Exposure to IoT platforms, telemetry systems, or real-time data processing
- Familiarity with MLOps concepts and model deployment workflows
- Contributions to open-source projects, technical blogs, or AI communities
What We Do
Nectir AI provides AI infrastructure for classrooms and campuses, enabling educators to create customizable, FERPA-compliant AI assistants within learning management systems. Its platform supports safe, secure interactions between educators and students and offers 24/7 personalized learning assistance grounded in course content. The company emphasizes academic integrity, privacy, and compliance, including FERPA and SOC 2 standards for institutions seeking trusted educational AI deployment.
