AI Engineer

You will design build and deploy production-grade AI systems including LLM-powered conversational agents RAG pipelines NLP workflows and voice AI integrations to deliver intelligent reliable and measurable AI solutions for enterprise clients across government financial services healthcare and telecommunications sectors so that Katas clients can automate customer interactions at scale with high accuracy low latency and strong business impact.

Qualifications :

Qualifications & Education : 

• Bachelors degree in Computer Science Artificial Intelligence Data Science Computational Linguistics or related field
• Masters degree in AI/ML is a plus
• Relevant certifications (GCP AI/ML etc.) are advantageous

Technical Skills : 

• LLM Integration: OpenAI GPT-4o Anthropic Claude Google Gemini or open-source models (LLaMA Mistral Qwen)
• AI Frameworks: LangChain LlamaIndex CrewAI or similar agent/RAG orchestration frameworks
• Prompt Engineering: System prompt design few-shot prompting chain-of-thought structured output (JSON mode function calling)
• RAG Pipelines: Document chunking embedding strategies retrieval optimization reranking
• Vector Databases: Pinecone Weaviate Qdrant or pgvector
• Voice AI: LiveKit Agents SDK STT integrations (Deepgram Google Speech-to-Text Whisper) TTS integrations (ElevenLabs Google TTS)
• Languages: Python (required); FastAPI for AI service exposure
• Cloud: GCP or Azure for AI/ML workload deployment Vertex AI Azure OpenAI Cloud Run
• Evaluation Frameworks: RAGAS DeepEval custom eval pipelines or LLM-as-judge approaches
• Containerization: Docker; basic Kubernetes for deploying AI services
• Monitoring: AI-specific observability LangSmith Langfuse or custom logging for tracing LLM calls in production

Additional Information :

Skills & Competencies : 

• Strong analytical thinking able to diagnose and improve AI system behavior through systematic evaluation and iteration
• Ability to balance research-oriented experimentation with production-grade engineering rigor
• Good communication skills able to explain AI system behavior limitations and tradeoffs clearly to non-technical Product and Project stakeholders
• Quality-first mindset proactively defines success metrics and failure modes before building
• Collaborative and cross-functional works closely with Backend Frontend and QA to ensure AI components integrate cleanly into the full product
• Agile/Scrum mindset with comfort operating in sprint-based delivery cycles
• Keeps up with the fast-moving AI landscape and proactively identifies relevant new tools models or techniques applicable to the team

Remote Work :

Yes

Employment Type :

Full-time