Associate Platform and Data Engineer

Reporting to Head, Platforms and Data Engineering, the Platforms and Data Engineer will work closely with Data Scientists, Threat/Malware Researchers, Project Managers and Infrastructure Engineers to develop and manage AI-powered agentic systems and data engineering solutions. The incumbent will be accountable for the design, development, deployment and maintenance of multi-agent AI platforms, including agent orchestration workflows, RAG implementations, vector database management, and AI-driven analytics solutions.

Key Responsibilities:

• Familiarize with Ensign's business domain and objectives to develop and deploy data solutions that meet internal business requirements and the needs of partners and customers

• Design, develop, test, deploy operational data transformation processes, including async/real-time data processing workflows

• Design, develop, manage relational databases and vector databases for AI/ML applications

• Design and develop multi-agent AI systems using LangGraph/LangChain for agent orchestration and workflow management

• Implement and maintain RAG (Retrieval Augmented Generation) workflows with vector databases (e.g., pgvector, ChromaDB) for semantic search and knowledge retrieval

• Integrate LLM APIs and manage prompt engineering for agent behaviors and AI-driven analytics

• Provide monitoring, maintenance and support for data operations as part of maintenance & support as required in client projects

• Manage development, staging, production environments to provide overall system functionality, health, scalability, resiliency, and security

• Deliver detailed documentation and ensure quality throughout project lifecycle

Qualifications/Requirements:

• Bachelor's degree in Computer Science / Computer Engineering or equivalent

• Strong proficiency in Python programming for data engineering and AI/ML applications, with experience in async/await patterns and concurrent programming

• Experience with Bash scripting for automation and system tasks

• Experience with AI/ML frameworks such as LangGraph and LangChain for agent orchestration

• Experience with vector databases (e.g., pgvector, ChromaDB) and RAG implementation patterns

• Basic understanding of REST APIs and async HTTP clients for integrating with external services

• Experience with LLM API integration (e.g., Google Gemini, OpenAI) and prompt engineering

• Familiarity with Pydantic for data validation and structured data modeling

• Understanding of modern software engineering tools such as Git, GitLab

• Familiarity with Docker, Kubernetes and cloud services (AWS)

• Familiarity with network concepts

• Comfort and experience working in Linux environment

• Aptitude for automation and software profiling

• Proven ability to handle multiple customer projects concurrently

• Detail-oriented, solution-focused and problem solver

• Willingness to continuously learn and adapt to rapidly evolving AI/ML tools and technologies

Preferred Skills (Good to haves):

• Around 1 year of experience developing data engineering pipelines

• Experience with Spark, Go, or other data engineering programming languages

• Knowledge of different data platforms (e.g. Kafka, MongoDB, Postgres, Elasticsearch), associated tools and cloud-based technologies (e.g. Lambda, Glue)

• Have strong knowledge in DevSecOps to design, develop, test, and deploy applications for customer projects

• Experience in Cyber Security / Telco industry will be an advantage

• Knowledge in Agile and CI/CD is desirable

• Familiarity with virtualization platform (Proxmox, VMware, KVM)

• Familiarity with Hadoop ecosystem and MPP databases

• Ability to demonstrate programming skills and knowledge without being overly dependent on AI