Job Description

CyRAACS is a leading technology and AI-led consulting firm specializing in Governance, Risk, and

Compliance (GRC) and Vulnerability Assessment services. A key product offering of CyRAACS is an

innovative AI-enabled SaaS platform tailored for GRC and CyberSecurity, designed to empower our clients

with self-service capabilities. We are looking for a highly skilled and motivated AI Platform Developer to join

our growing technology team and contribute to the development of a high-quality, robust, and user-friendly

platform.

Role Overview

As an AI Platform Engineer at CyRAACS, you will play a crucial role in the design, development and deployment of the AI foundation for the CyRAACS digital platform. You'll be responsible for data pipelines, data models, and API services that will be used by Application Development teams to build enterprise class mission critical applications. This is an exciting opportunity for someone who thrives in a fast-paced environment, possesses strong technical skills, and has a passion for building innovative, cloud-native applications.

Role Overview

As an AI Platform Engineer at CyRAACS, you will play a crucial role in the design, development and

deployment of the AI foundation for the CyRAACS digital platform. You'll be responsible for data pipelines, data models, and API services that will be used by Application Development teams to build enterprise class mission critical applications. This is an exciting opportunity for someone who thrives in a fast-paced environment, possesses strong technical skills, and has a passion for building innovative, cloud-native applications.

Key Responsibilities

Build, sustain and evolve the enterprise AI architecture along with head of Engineering, from
model lifecycle to governance to business integration.
Build shared AI services and product features for CyRAACS SaaS platform and other service
portals
Oversee and own adjacent AI adjacent initiatives at CyRAACS such as Machine learning models , ML Ops, Data Science , Analytics and Automation initiatives Build modular pipelines (RAG, agentic flows, auto-evidence collection) and ensure safe reuse
across domains.
Build privacy preserving pipelines , enforce tenant isolation, and design secure feedback loops. Establish AI logs, traceability, and fairness controls. Design and embed AI into analyst and consultant workflows (e.g., MCP automation, TPRM
analysis agents).
Provide architectural and deployment/post deployment inputs on vector DBs, PEFT fine-tuning, RAG orchestration, model hosting. Integrate and build containers that can be deployed in production (Docker, Kubernetes etc.)

Core Requirements

3-5 years of experience with end-to-end AI/ML design and operationalization with excellent
communication skills and attention to detail.
Bachelors' or Masters degree in AI /Machine learning/Data Science/Statistics or an adjacent
quantitative field
Proficiency in Python, Java ,frameworks such as FastAPI, LangChain, vector databases (Qdrant,
Weaviate), and embedding models.
Familiarity or Proficiency with AI developer tools such as Windsurf/Cursor/Claude code as well
as UI/UX design /Planning /Testing tools
Proficiency in model deployment /inferencing on cloud platforms (AWS or Azure/Vertex AI
stacks)
Ability to translate complex AI patterns into business value generating features and safe automation. Up to date with AI Research and trends and be able to translate papers into implementable code
for early AI adoption.
Proven work in agent-based automation, privacy-enhancing techniques, and AI DevOps.

Core Requirements

3-5 years of experience with end-to-end AI/ML design and operationalization with excellent
communication skills and attention to detail.
Bachelors' or Masters degree in AI /Machine learning/Data Science/Statistics or an adjacent
quantitative field
Proficiency in Python, Java ,frameworks such as FastAPI, LangChain, vector databases (Qdrant,
Weaviate), and embedding models.
Familiarity or Proficiency with AI developer tools such as Windsurf/Cursor/Claude code as well
as UI/UX design /Planning /Testing tools
Proficiency in model deployment /inferencing on cloud platforms (AWS or Azure/Vertex AI
stacks)
Ability to translate complex AI patterns into business value generating features and safe automation. Up to date with AI Research and trends and be able to translate papers into implementable code
for early AI adoption.
* Proven work in agent-based automation, privacy-enhancing techniques, and AI DevOps.