Agentic AI Engineer

Who we are: -

At CitiusTech, we constantly strive to solve the industry's greatest challenges with technology, creativity, and agility. With over 8,500 healthcare technology professionals worldwide, CitiusTech powers healthcare digital innovation, business transformation, and industry-wide convergence for over 140 organizations through next-generation technologies, solutions, and products. We aim to accelerate the transition to a human-first, sustainable, and digital healthcare ecosystem with the world's leading Healthcare and life sciences organizations and our partners.

Here is an opportunity for you to make a difference and collaborate with global leaders to shape the future of healthcare and positively impact human lives.

Our vision: -

To inspire new possibilities for the health ecosystem with technology and human ingenuity.

Responsibilities: -

Design, build, and productionize ML models for personalization, forecasting, anomaly detection, and NLP on Google Cloud Platform (Vertex AI, BigQuery ML, Dataflow).

Develop scalable data and feature pipelines; implement feature stores (Feast) and streaming ingestion (Pub/Sub, Kafka) for real-time inference.

Implement agentic AI patterns: multi-agent orchestration, tool-use, retrieval-augmented generation (RAG), and function calling with guardrails (policy/PII filters).

Optimize online inference for latency and cost using Vertex AI Endpoints, GPU/TPU where applicable, and autoscaling on GKE.

Establish experiment frameworks (A/B, interleaving, bandits) and offline evaluation (precision/recall, ROC-AUC, NDCG, MAP).

Integrate vector search (Vertex Matching Engine / FAISS / Elasticsearch) for semantic retrieval and recommendations.

Ensure privacy, security, and compliance (GDPR/CCPA); apply differential privacy where needed and follow model governance practices.

Document designs, review code, and collaborate with product, data engineering, and platform teams.

Desired Technical Skills

Languages: Python (primary), Java/Scala (nice to have).

Frameworks: TensorFlow, PyTorch, scikit-learn; JAX optional.

Pipelines & Features: Apache Beam/Dataflow, Airflow/Cloud Composer, Feast.

RAG & Agents: LangChain/LlamaIndex, function calling, toolformer patterns, vector DBs (FAISS, Chroma, Elasticsearch).

Data & Streaming: BigQuery, Spark, Kafka, Pub/Sub.

Serving: Vertex AI Endpoints, KFServing, Triton;

Docker, Kubernetes (GKE).

Observability: MLflow, Vertex Experiments/Model Registry, Prometheus, Grafana.

Cloud: Google Cloud Platform (Vertex AI, BigQuery, GCS) primary; familiarity with AWS (SageMaker) and Azure ML.

Preferred Experience & Capabilities

Delivered ML systems at scale (batch + real-time) with measurable business impact.

Hands-on with vector search, RAG, and agentic workflows using tools/actions and governance (safety filters, jailbreak protection).

Expertise in feature engineering, data quality, and drift detection (data/model).

Strong understanding of IR/ranking metrics and online experimentation.

Ability to mentor, perform code reviews, and contribute to architectural decisions.

Excellent communication with cross-functional stakeholders.

Note: Primary development environment is Google Cloud Platform (Google Cloud Platform). Flexibility to work with AWS and Azure is desired for portability and interoperability.

Life at CitiusTech

We focus on building highly motivated engineering teams and thought leaders with an entrepreneurial mindset, centered on our core values of Passion, Respect, Openness, Unity, and Depth (PROUD) of knowledge. Our success lies in creating a fun, transparent, non-hierarchical, diverse work culture that focuses on continuous learning and work-life balance.

Rated by our employees as the Great Place to Work for according to the Great Place to Work survey. We offer you a comprehensive set of benefits to ensure that you have a long and rewarding career with us.

Join CitiusTech. Be You. Be Awesome.