Senior AI/ML Engineer (SaaS / AI & Data)
Summary
Hired via Atlantis Consulting for a US software development firm, this engineer builds production-grade AI features across a portfolio of SaaS businesses — integrating LLM APIs (OpenAI, Anthropic), model serving, pipelines and RAG systems, mostly in Python on AWS/GCP/Azure. Reports to an AI Program Lead and works directly with executives.
About the job Senior AI/ML Engineer (SaaS / AI & Data)
Location: NCR,Manila, Philippines. Remote.
Company:US-based Software Development Firm
Position Type:Full-Time
Reporting to:AI Program Lead
Job Brief
Atlantis Consulting is partnering with a leading US-based software development firm to hire a Senior AI/ML Engineer who will play a critical role in building and scaling AI capabilities across a portfolio of SaaS businesses.
This is a high-impact, builder role—focused on shipping production-grade AI solutions (not prototypes) that directly drive revenue, retention, and operational efficiency. You will work closely with executive stakeholders and deploy AI systems across multiple business units, creating compounding value through reusable architecture.
Responsibilities
AI Product Development
- Design and deploy AI/ML features embedded in SaaS products (document intelligence, automation, predictive analytics, AI-assisted UX)
- Integrate LLM APIs (OpenAI, Anthropic, etc.) into production-ready applications
- Own end-to-end development lifecycle: discovery, build, test, deploy, iterate
- Build reusable AI components that scale across multiple companies
- Partner with leadership to prioritize initiatives based on ROI and feasibility
- Support internal AI stakeholders across business units
- Build and maintain AI infrastructure (model serving, pipelines, prompt systems)
- Ensure strong data foundations for AI initiatives across platforms
- Implement evaluation frameworks to monitor model performance
Stakeholder Management & Translation
- Translate business problems into scalable AI solutions
- Communicate technical trade-offs, risks, and timelines to executives
- Collaborate directly with senior leadership and product teams
Knowledge Building & AI Playbook Development
- Contribute to internal AI best practices and frameworks
- Document scalable solutions to drive long-term portfolio value
Requirements
- 5-10+ years in software engineering; 2+ years in AI/ML production environments
- Proven experience integrating LLM APIs into real-world applications
- Strong proficiency in Python and modern AI tooling (LangChain, LlamaIndex, vector DBs)
- Experience with AWS, GCP, or Azure and containerization (Docker/Kubernetes)
- Ability to manage multiple projects across different business units
- Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience)
Preferred
- Background in SaaS, B2B, or vertical market software
- Experience with agentic AI systems and multi-step reasoning pipelines
- Strong exposure to RAG architectures and vector search
- Familiarity with no-code/low-code tools (Zapier, Make, n8n)
- Experience in multi-entity or portfolio-based environments
Build AI That Scales Across Businesses
This is not a typical engineering role—you will operate at the intersection of AI, product, and business impact. Every solution you build has multiplier effects across multiple companies, giving you unmatched exposure, ownership, and influence. You'll work directly with decision-makers and shape how AI drives real commercial outcomes.