AI Engineer

Overview:

We are looking for an AI Engineer (AI Engineer – Conversational AI & Application Development).

The candidate will need to be collaborative, organised, think out-of-the-box, and be ready to pursue new opportunities. Most importantly, this role is for an individual who is passionate about making a difference through healthcare.

Role Summary

talented AI Engineer

Key Responsibilities

Design and build multi‑agent conversational systems

- Collaborate with product managers, designers, and engineers to define user journeys, agent capabilities, and integration points.

- Develop robust, scalable backend services and APIs (Python/Golang/Node.js/Java) to power AI agents and orchestration workflows.

- Apply advanced Natural Language Processing (NLP), Retrieval‑Augmented Generation (RAG), and LLM fine‑tuning techniques for intent recognition, entity extraction, and dynamic dialogue management.

Deploy and operate conversational workloads on GCP Cloud Run (serverless) and Kubernetes (GKE)

Leverage BigQuery

Design and develop interactive dashboards in Power BI or Tableau

- Integrate conversational agents with enterprise systems (databases, CRMs, ERPs) and third‑party APIs.

Arize Phoenix, Langfuse, and LangSmith

- Contribute to the full software development lifecycle: requirements, architecture, coding, testing, CI/CD, deployment, and maintenance.

- Troubleshoot and resolve production issues to ensure high availability and optimal performance.

- Document technical designs, decisions, and model specifications for cross‑functional reference.

Required Qualifications

- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, or a related field.

one or more

Python

Java

Node.js

Go

- Experience building RESTful or GraphQL APIs and designing microservices.

- Solid grasp of machine‑learning fundamentals: supervised/unsupervised learning, evaluation metrics, feature engineering.

- Familiarity with modern NLP libraries (spaCy, Haystack, Hugging Face Transformers, LlamaIndex).

- Strong version‑control habits (Git, trunk‑based development) and CI/CD pipelines.

- Excellent problem‑solving, communication, and collaboration skills.

- Passion for continuous learning and adapting to emerging AI technologies.

Preferred Qualifications

AI chat agents or virtual assistants

LangGraph, AutoGen, CrewAI, ADK

- Experience with Large Language Models (Gemini, GPT‑4, Claude, Mistral, etc.) and vector databases (Weaviate, Chroma, Pinecone).

Deep experience with Google Cloud Platform (GCP):

BigQuery

Cloud Run (serverless)

Google Kubernetes Engine (GKE)

Identity and Access Management (IAM)

Business‑intelligence expertise

- Familiarity with other cloud providers (AWS, Azure) and their AI/ML services.

MLOps

- Database skills in both SQL (PostgreSQL, BigQuery) and NoSQL (Firestore, DynamoDB).

- Contributions to open‑source AI/ML projects or technical blogging/presentations.