AI Platform Engineer

• Design build and operate services in the central AI platform. Every service should have clear API contracts versioning and SLOs from day one.
• Write production Python for AI services. Contribute to shared libraries SDKs and integration patterns that product teams will consume.
• Instrument everything: cost tagging per request latency and error metrics quality signals and audit logs. If it is not measured it is not shipped.
• Own on-call rotation for the AI platform services you build. Author runbooks and improve them after every incident.

• Work directly with product engineering leads across the product lines to onboard their AI features onto the central platform.
• Provide technical support integration guidance and troubleshooting to product teams consuming platform services.
• Contribute to Architecture Decision Records. Push back on decisions you disagree with; document tradeoffs.

• Set the operational bar: observability alerting incident response and post-incident reviews.
• Own vendor evaluation for tools in your area of specialization. Run bakeoffs when the choice is not obvious. Make cost quality and reliability tradeoffs explicit.
• Contribute to the AI security posture: PII handling tenant isolation prompt injection defense and audit logging within your services.

• The AI-forward end of the platform. You build the retrieval prompt and guardrail systems that make LLM output good enough to ship to customers.
• RAG-as-a-service platform: ingestion chunking embedding retrieval quality and hybrid search.
• Prompt engineering at scale: templates evaluation versioning and per-tenant customization.
• Guardrails and content safety: input filtering output validation PII redaction tool-use sandboxing.
• Agent frameworks and tool-use patterns as agent workflows move into production across product lines.
• Domain-specific fine-tuning experiments and quality benchmarking.

• Multi-provider model gateway with routing fallback retry and rate-limit logic.
• Prompt registry versioning and rollout controls (canary feature flags).
• Shared libraries and SDKs for product-team consumption. API contracts versioning deprecation strategy.
• Tenant isolation architecture: how customer data flows through platform services safely.
• Cost attribution and budget enforcement at the gateway layer.

• Observability platform: prompt and response tracing cost per request quality signals drift detection.
• Evaluation infrastructure: golden datasets offline evals LLM-as-judge patterns regression testing.
• Model deployment pipelines including fine-tuned models where applicable.
• Alerting and SLO framework for AI services. Distinct from general engineering SLOs: quality regression is a first-class alert.
• Fine-tuning and RLHF pipelines when product-specific tuning becomes justified.

• Bachelors or Masters degree in Computer Science Engineering or equivalent.
• 5 years of professional software engineering experience with a strong production track record.
• 6 years building production distributed systems ideally including internal developer platforms or API gateways at scale.
• 5 years in MLOps LLMOps ML platform engineering or a hybrid DevOps plus ML role at production scale.
• Hands on experience with observability tools for LLM systems: LangSmith Langfuse Braintrust Arize or comparable.
• Workingknowledge of evaluation methodology for LLM systems: benchmark design LLM-as-judge human review workflows
• Workingfluency in the modern LLM ecosystem: OpenAI or Anthropic APIs at least one orchestration framework (LangChain LlamaIndex or equivalent) at least one vector database at least one observability tool.
• 2 years of hands-on production experience with LLM-based systems: prompt engineering RAG evaluation or LLM infrastructure.
• Strong Python and one of Go or Java. Comfortable with async patterns backpressure and rate limiting. Comfortable writing production code not just notebooks or scripts.
• Experience designing multi-tenant systems with hard isolation guarantees.
• Cloud-native depth on Azure or AWS: Kubernetes service mesh IaC (Terraform) CI/CD.
• Experience shipping model updates safely in production: canaries shadow evaluation rollback triggers.
• Comfort with the full ML lifecycle: training pipelines serving infra monitoring and cost management.
• Strong grasp of AI security fundamentals: PII handling tenant isolation prompt injection basics.
• Ability to communicate technical decisions clearly in async writing. This role is distributed across time zones and cannot be run on synchronous meetings alone.
• Fluent English language skills

• Domain experience in procure-to-pay ERP integration accounts payable procurement or adjacent finance and operations software.
• Experience at a product company or PE-backed B2B SaaS ideally on an internal platform team.
• Contributions to open-source AI/ML infrastructure projects.
• Experience with agent frameworks (LangGraph AutoGen CrewAI or custom orchestration) in production.
• Prior experience on a founding platform team where you shipped v1 of a service used by multiple internal customers.

About the Company

We are a global team of innovators and advocates transforming how financial data is captured stored and manipulated with our comprehensive suite of automation technology. Our platform seamlessly integrates with your existing ERP for an unrivaled end-user experience. We do the heavy lifting so accounting procurement and fundraising teams can do their best work.

PairSofts aspires to be the strongest procure-to-pay platform for the mid-market and enterprise with close integration to Microsoft Dynamics Blackbaud Oracle SAP Acumatica and Sage ERPs.

At PairSoft we are passionate about innovation transparency diversity and advocating on behalf of our customers and communities we support. We offer exciting career opportunities and a collaborative culture that allows individuals to learn grow and create meaningful impact. We are expanding and seeking team players who are eager to jump in and contribute to our rapid growth!

PairSoft is proud to be an equal opportunity workplace. We are committed to equal employment opportunity regardless of race color ancestry religion sex national origin sexual orientation age citizenship marital status disability gender identity veteran status or any other protected status. We also consider qualified applicants regardless of criminal histories consistent with legal requirements. If you have a disability or special need that requires accommodation please email us at:

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