Website:
appxcess.com
Job details:
Job Title: AI Full Stack Engineer
Employment Type: Full-Time
Location: Remote
Experience: 2–5 Years
AppXcess Technologies is seeking a highly capable AI Full Stack Engineer to design, develop, and deploy intelligent AI-driven applications, with a strong focus on Conversational AI, Retrieval-Augmented Generation (RAG), and enterprise-grade AI systems.
This role is ideal for engineers who have hands-on experience delivering production-ready AI applications, including chatbots, AI assistants, and knowledge-driven platforms. You will work across the full stack—frontend, backend, and AI/ML systems—while leveraging modern frameworks and cloud platforms such as Microsoft Azure.
Key Responsibilities
AI/ML Development
- Design, build, and deploy LLM-powered applications, including chatbots, copilots, and AI assistants
- Develop and productionize RAG pipelines including ingestion, chunking, embeddings, vector storage, retrieval, re-ranking, and response generation
- Fine-tune, evaluate, and optimize LLMs for real-world use cases
- Implement prompt engineering, domain adaptation techniques (LoRA, PEFT), and model optimization strategies
- Build multimodal AI systems integrating text, structured data, and images
- Integrate and evaluate speech-to-text (STT) and text-to-speech (TTS) systems for conversational interfaces
- Optimize AI models for accuracy, latency, cost, and scalability
Full Stack & System Development
- Develop backend services using Python (FastAPI) and scalable API architectures
- Build responsive frontend applications using React / Next.js
- Design and maintain APIs for AI services, tools, and external integrations
- Implement caching, batching, and request optimization for LLM workloads
- Ensure clean, modular, and maintainable code across the stack
AI Infrastructure & MLOps
- Build and maintain production-grade AI pipelines including training, evaluation, deployment, and monitoring
- Implement LLMOps / MLOps practices (CI/CD, model versioning, experiment tracking)
- Develop continuous learning workflows with feedback loops and retraining strategies
- Work with Azure services such as:
- Azure OpenAI
- Azure AI Search (vector/hybrid search)
- Azure Machine Learning
- Azure AI Services / Cognitive Services
- Ensure observability using logging, metrics, tracing, and alerting
Data Engineering for AI
- Process and manage structured and unstructured datasets
- Build pipelines for data ingestion, preprocessing, enrichment, and validation
- Handle noisy, incomplete, or imbalanced data effectively
- Implement data privacy, security, and compliance controls (PII handling, GDPR/HIPAA awareness)
- Design synthetic data generation strategies where required
Evaluation, Governance & Reliability
- Develop evaluation frameworks (accuracy, recall, BLEU, ROUGE, etc.)
- Monitor and improve model performance, bias, drift, and explainability
- Implement testing strategies for AI pipelines (unit, integration, system testing)
- Apply responsible AI practices, including fairness, safety, and compliance
- Ensure robust error handling and production reliability
Collaboration & Agile Execution
- Work in Agile environments (sprints, stand-ups, reviews)
- Collaborate with product managers, designers, and engineers to deliver end-to-end solutions
- Translate business requirements into scalable AI architectures
- Maintain clear documentation for design, implementation, and workflows
Innovation & Continuos Learning
- Stay updated with advancements in GenAI, LLMs, multimodal AI, and conversational systems
- Evaluate emerging tools (Hugging Face, LangChain, OpenAI, etc.)
- Contribute to internal knowledge sharing, demos, and architectural discussions
- Identify opportunities to improve scalability, performance, and impact of AI systems
Required Qualifications
Education & Experience
- Bachelor’s or Master’s degree in Computer Science, AI, ML, or related field
- 2–5 years of experience in AI/ML engineering or full stack development
- Proven experience delivering production-grade AI applications
- Hands-on experience building chatbots, conversational AI, or RAG-based systems
Technical Skills
- Strong proficiency in Python and frameworks like FastAPI
- Experience with React / Next.js (full stack capability preferred)
- Hands-on experience with:
- LLMs, embeddings, and prompt engineering
- RAG systems and vector databases (FAISS, Pinecone, Weaviate, etc.)
- NLP/NLU techniques and modern AI frameworks
- Familiarity with Azure AI ecosystem (Azure OpenAI, AI Search, ML services)
- Experience with STT/TTS tools (e.g., Whisper, ElevenLabs)
- Knowledge of PyTorch / TensorFlow
- Understanding of API design, microservices, and system scalability
- Familiarity with Docker, CI/CD, and deployment workflows
Nice to Have
- Experience with agent frameworks (LangChain, LlamaIndex, Semantic Kernel)
- Exposure to multimodal AI systems
- Experience with voice assistants or healthcare/enterprise AI systems
- Familiarity with evaluation tools (RAGAS, DeepEval)
- Experience with Kubernetes or distributed systems
- Azure certifications (AI Engineer / Data Scientist)
Professional Attributes
- Strong problem-solving and analytical thinking
- High ownership and accountability
- Effective communication with technical and non-technical stakeholders
- Attention to detail in reproducibility, safety, and compliance
- Ability to work in a fast-paced, collaborative environment
What We Offer
- Opportunity to work on cutting-edge Generative AI and RAG systems
- Exposure to real-world AI implementations across industries
- High ownership and impact-driven role
- Fast-paced, innovation-focused environment
- Continuous learning and growth in AI and full stack technologies
Click on Apply to know more.