About the role
We are looking for an AI Engineer to join our engineering team and help build intelligent products and automation systems at Appnox. You will work across the full AI development lifecycle, from experimenting with models and designing prompts to building retrieval pipelines, integrating AI services, and deploying reliable production systems. You will collaborate closely with backend engineers and product teams to turn business requirements into practical AI solutions.
What you'll do
- Design and develop AI-powered features using modern LLMs and AI technologies
- Build and integrate LLM-based applications, AI agents, and intelligent automation workflows
- Develop retrieval-augmented generation (RAG) pipelines and work with vector databases
- Experiment with prompting, model selection, evaluation, and response quality
- Integrate third-party AI APIs and open-source models into production applications
- Build APIs and backend services that support AI-powered products
- Work with embeddings, semantic search, document processing, and knowledge bases
- Monitor and improve the reliability, latency, and cost of AI applications
- Collaborate with backend engineers, frontend developers, and product teams
- Write clean, maintainable, well-tested production code
- Research emerging AI technologies and identify practical opportunities for their use
- Debug and improve AI systems based on real-world usage and feedback
What we're looking for
- 0-1 year of experience in AI/ML, backend engineering, or a related field
- Strong programming skills in Python
- Good understanding of APIs, databases, and backend application development
- Hands-on experience working with LLMs and generative AI
- Understanding of prompt engineering and LLM application development
- Familiarity with embeddings, vector databases, and semantic search
- Experience integrating third-party APIs and AI/ML services
- Understanding of software engineering principles and Git-based workflows
- Ability to debug problems and work independently on technical challenges
- Good communication and collaboration skills
- Strong willingness to learn and experiment with new technologies
Nice to have
- Experience building RAG-based applications
- Experience with LangChain, LlamaIndex, or similar frameworks
- Experience with OpenAI, Anthropic, Google Gemini, Mistral, or other LLM APIs
- Experience with open-source models and Ollama
- Experience with PostgreSQL, pgvector, Redis, or Elasticsearch
- Experience with Docker and cloud deployment
- Understanding of AI evaluation and observability
- Experience with OCR, document processing, or multimodal AI
- Experience building AI agents and tool-calling workflows
- Experience with Laravel, Node.js, or other backend frameworks
What we offer
- Opportunity to work on real-world AI products and automation systems
- Hands-on exposure to modern LLM and AI technologies
- Ownership of meaningful engineering projects from development to production
- Collaborative environment with backend, frontend, AI, and product teams
- Opportunity to experiment with emerging AI technologies
- Learning and growth opportunities across AI and software engineering
- Flexible hybrid working environment
- Opportunity to work on products used by real businesses
- A culture focused on engineering quality, experimentation, and continuous improvement
Hiring process
- 01Application Review
- 02Technical Screening
- 03AI/Engineering Technical Interview
- 04Technical Deep Dive
- 05Culture & Team Discussion
- 06Final Interview
- 07Offer