AI Developer - Mid-Level

About PhotonX Technologies

PhotonX is a fast-growing product and engineering company focused on digital product design and enterprise web and mobile applications. We build customer-facing and internal SaaS experiences across B2B and B2C domains, specialising in UI/UX design, full‑stack development, and Webflow solutions. Our mission is to deliver polished, user-centred interfaces that drive adoption and retention.

Location

Hyderabad — This is a fully on-site role based at our Hyderabad office. Remote or hybrid arrangements are not available; candidates must be prepared to commute to the office daily.

Work Schedule

This position follows a mandatory six-day workweek: Monday–Saturday, 10:00 AM to 8:00 PM. Attendance in the Hyderabad office is required for all scheduled workdays. Occasional variations for business needs may occur and will be communicated in advance.

Experience Required

2–5 years of professional experience in AI/ML development with a proven track record of delivering production-grade AI solutions.

Job Summary

We are seeking experienced AI Developers to lead the design, development, and deployment of intelligent software solutions. You will architect and implement complex AI/ML systems, mentor junior developers, and drive innovation in our AI initiatives. This role requires expertise in GenAI, large language models (LLMs), and production-scale AI deployments, with the ability to translate business requirements into robust technical solutions.

Key Responsibilities

AI/ML Development & Architecture

• Design, develop, and deploy production-grade AI/ML models and systems.
• Architect and implement RAG (Retrieval-Augmented Generation) pipelines for enterprise applications.
• Lead prompt engineering initiatives and optimise LLM workflows for performance and cost efficiency.
• Design and implement embedding strategies and manage vector databases (Pinecone, Weaviate, Chroma, Qdrant).
• Build and deploy GenAI solutions using state-of-the-art language models (GPT-4, Claude, Gemini, Llama).
• Conduct model training, fine-tuning, evaluation, and hyperparameter optimisation.
• Implement model monitoring, A/B testing, and continuous improvement strategies.
  
  

System Integration and Production Deployment

• Design and implement scalable backend services and APIs for AI model integration.
• Build robust deployment pipelines using FastAPI, Flask, or similar frameworks.
• Containerise applications with Docker and orchestrate with Kubernetes.
• Deploy and manage AI infrastructure on cloud platforms (AWS, Azure, GCP).
• Optimise model performance, latency, and cost for production environments.
• Implement CI/CD pipelines for automated model deployment and monitoring.
• Ensure security, compliance, and data privacy in AI systems.
  
  

Technical Leadership & Collaboration

• Lead technical discussions and provide architectural guidance on AI projects.
• Mentor junior AI developers and conduct code reviews.
• Collaborate with product managers, UI/UX designers, and full-stack developers to define AI features.
• Translate business requirements into technical specifications and implementation plans.
• Prepare comprehensive documentation for system architecture, APIs, and workflows.
• Present technical solutions and progress updates to stakeholders.
  
  

Research and Innovation

• Stay current with the latest AI research, frameworks, and industry best practices.
• Evaluate and integrate new AI techniques and tools to improve product capabilities.
• Drive proof-of-concept initiatives for emerging AI technologies.
• Contribute to the development of internal AI frameworks and best practices.
  
  

Required Qualifications

Education

• B.Tech, B.E, MCA, M.Tech, or M.S. in Computer Science, AI, Data Science, or related field.
• Strong academic background with relevant AI/ML coursework.
  
  

Essential Requirements

• 2–5 years of professional experience building and deploying AI/ML solutions in production.
• Proven track record of delivering end-to-end AI projects from conception to deployment.
• Expert-level proficiency in Python and modern software engineering practices.
• Deep understanding of machine learning algorithms, model evaluation, and statistical methods.
• Hands-on production experience with deep learning frameworks (TensorFlow and/or PyTorch).
• Demonstrable expertise in GenAI, LLMs, embeddings, and vector databases.
• Strong experience with RAG pipelines and prompt engineering techniques.
• Proficiency with Git, Linux/Unix, and modern development workflows.
• Experience with API development and microservices architecture.
• Strong problem-solving skills and ability to debug complex AI systems.
• Excellent communication skills and ability to work in cross-functional teams.
• Mandatory: This is a full-time, on-site role requiring availability to work six days per week (Monday–Saturday, 10:00 AM–8:00 PM). Remote or hybrid work arrangements are not available.
  
  

Preferred Qualifications

• Production experience with LangChain, LlamaIndex, or similar orchestration frameworks.
• Experience with model fine-tuning and custom training pipelines.
• Contributions to open-source AI projects or published research papers.
• Active participation in Kaggle competitions, AI hackathons, or ML conferences.
• Experience with MLOps practices and tools (MLflow, Weights & Biases, Kubeflow).
• Knowledge of model compression, quantisation, and edge deployment.
• Experience with multi-modal AI systems (text, image, audio).
• Familiarity with AI safety, alignment, and responsible AI practices.
  
  

Technical Skills

Programming and Frameworks

• Must: Python (advanced), TensorFlow and/or PyTorch, NumPy, Pandas, scikit-learn.
• Highly desired: Hugging Face Transformers, LangChain, LlamaIndex, FastAPI or Flask.
• Nice to have: OpenCV, spaCy, CUDA programming, Rust or C++ for performance optimisation.
  
  

AI/ML Specific

• Must: Advanced machine learning algorithms, deep learning architectures, neural networks, GenAI, LLMs, embeddings, vector databases, RAG pipelines, prompt engineering.
• Highly desired: Model fine-tuning, transfer learning, reinforcement learning, model evaluation and optimisation.
• Nice to have: Multi-modal models, diffusion models, AI agents, knowledge graphs.
  
  

Deployment and Infrastructure

• Must: Git, Linux/Unix, FastAPI or Flask, REST APIs, Docker, cloud platforms (AWS, Azure, or GCP).
• Highly desired: Kubernetes, CI/CD pipelines, infrastructure as code (Terraform, CloudFormation), model serving frameworks (TorchServe, TensorFlow Serving).
• Nice to have: Serverless architectures, streaming data pipelines, monitoring and observability tools (Prometheus, Grafana).
  
  

Required Skills Summary

• Advanced Python programming and software engineering best practices.
• Production experience with machine learning and deep learning frameworks.
• Expert knowledge of GenAI, LLMs, embeddings, vector databases, and RAG systems.
• Hands-on experience with model deployment, APIs, and cloud infrastructure.
• Strong system design and architecture skills.
• Leadership and mentorship capabilities.
  
  

What We Offer

• Opportunity to lead cutting-edge AI projects for SaaS and enterprise clients.
• Work with the latest GenAI and LLM technologies at scale.
• Leadership role with mentorship and career advancement opportunities.
• Collaborative, innovation-driven work environment.
• Exposure to diverse AI use cases across multiple industries.
• Professional development support, including conferences and certifications.
• Competitive compensation package with performance incentives.
• Opportunity to shape the AI strategy and technical direction of the company.
  
  

Skills: docker,rust,tensorflow,pandas,python,pytorch,spacy,fastapi,langchain,git,flask,cuda,numpy,prompt engineering,scikit-learn,aws,genai,opencv