We are seeking a Software Engineering Professional to join our AI Factory, responsible for designing, building, deploying, and operating AIāpowered solutions at scale.
Requirements
- Design and build AI driven services, agents, and copilots using LLMs, embeddings, vector databases, and orchestration frameworks
- Develop and deploy agent based architectures, including tool calling, workflow agents, and multi agent systems
- Integrate AI capabilities into enterprise platforms and digital products using APIs and event driven patterns
- Apply prompt engineering, retrieval augmented generation (RAG), and evaluation techniques to ensure accuracy and reliability
- Design and manage AI environments (Dev / Test / Beta / Prod) with clear separation, controls, and promotion paths
- Implement environment guardrails covering access control, data isolation, token usage, cost limits, and compliance
- Define reusable environment blueprints and deployment patterns for AI workloads
- Support multi tenant and multi use case AI platforms with chargeback/showback models
- Build and maintain CI/CD pipelines for AI and agent deployments, including model, prompt, and configuration versioning
- Automate testing, validation, and rollout of AI services using infrastructure as code and pipeline automation
- Implement monitoring and observability for AI systems (latency, cost, drift, quality, failures)
- Ensure reliability, scalability, and resilience of AI workloads in production
- Leverage AI tools and copilots to accelerate software development, testing, documentation, and code review
- Embed AI into developer workflows to improve productivity, quality, and time to market
- Champion best practices for secure and responsible use of AI in software engineering
- Continuously evaluate emerging AI engineering tools and frameworks
- Ensure AI solutions comply with security, privacy, and responsible AI standards
- Implement controls for data usage, prompt safety, hallucination mitigation, and auditability
- Contribute to AI governance frameworks covering lifecycle management, approvals, and risk management
- Partner with product owners, architects, platform teams, and business stakeholders to deliver AI use cases
- Provide technical leadership and mentoring on AI engineering and DevOps practices
- Contribute to reusable assets, reference architectures, and internal AI standards
Benefits
- Competitive salary
- Stock options or equivalent
- Health insurance
- Dental insurance
- Vision insurance
- Retirement plan
- Life insurance
- Disability insurance
- Paid time off
- Holidays
- Flexible working hours
- Remote work options
- Wellness programs
- Education assistance
- Professional development opportunities
