Senior Software Engineer – AI Build and Deployment

Apr 30, 2026

About Us:

Compliance & Risks is the leading provider of market access and product compliance SaaS solutions and is recognized as the leading end-to-end global product compliance solution provider across the technology, consumer goods and retail, industrial goods and life sciences sectors. The company’s market leading SaaS platform, C2P, enables uninterrupted market access for enterprises selling products globally by monitoring and managing key product requirements, regulations and standards in their chosen markets. The C2P platform provides the world’s most comprehensive database of legislative information, insights and actions, linked to product workflows, to help clients bring products to markets faster with lower risk and ensure ongoing compliance.

The company serves over 220+ global enterprise customers including: GE, Google, Nike, Amazon, Ikea, Bose, Tesla, Vaillant, Unisys, Samsung and Fujitsu.

Our Values:

All employees should continually promote legacy of Company Culture through demonstrating its values – 1. Trust 2. Respect 3. Winning Together 4. Innovation

Compliance & Risks is an Equal Opportunities Employer.

Purpose:

The Senior Software Engineer will be responsible for building and deploying cutting-edge AI solutions into real-time user applications and high-volume pipelines. We use a combination of serverless and AWS infrastructure fully defined as code, and continuously integrated and deployed.

We are early adopters of agentic coding tools to drive both velocity and engineering excellence. We deliver value through modern agile DevOps principles – continuous delivery, metric tracking, and rapid user feedback.

We believe in long-term success by establishing a sustainable pace of development, flexible working hours, and setting enough time aside to take care of your physical and emotional well-being.

Responsibilities:

• Design and build production-grade AI/LLM processing pipelines (document ingestion, extraction, classification, summarization, RAG) with a focus on reliability, throughput, and unit economics.
• Own observability for AI workloads end-to-end — structured logs, metrics, traces, prompt/response capture, token and cost attribution, and quality evals — integrated with Datadog.
• Build and maintain the deployment and runtime infrastructure for these pipelines on AWS (EKS, Lambda, Step Functions, SQS/Kinesis, S3) using Infrastructure-as-Code (Terraform / CDK) with reusable, reviewable modules.
• Establish CI/CD for AI services and models: automated testing, regression evals, safe rollouts (canary / blue-green), and rollback paths for both code and prompt/model changes.
• Drive engineering excellence in the AI team — pipeline architecture patterns, versioning of prompts/models/datasets, reproducibility, and separation of batch vs. real-time paths.
• Partner with SRE, Platform, and Product Engineering to harden shared services (secrets, networking, identity, data access) and ensure AI workloads meet security and compliance requirements.
• Mentor engineers on building maintainable, testable AI systems; raise the bar on code review, design documents, and operational readiness reviews.
• Embed SOC 2 security and compliance practices into design and implementation decisions, proactively raising gaps in access control, logging, and data protection.

Requirements:

• 7+ years building production distributed systems, with at least 2+ years operating AI/ML or LLM-based pipelines at scale.
• Deep experience with AWS (EKS/Kubernetes, Lambda, Step Functions, event-driven patterns) and Terraform or AWS CDK as a primary delivery mechanism.
• Strong proficiency in Python (and ideally TypeScript/Node) with production patterns for async processing, backpressure, retries, and idempotency.
• Proven track record with observability stacks (especially LGTM) applied specifically to probabilistic/LLM systems — evals, drift, hallucination detection, cost/latency SLOs.
• Experience integrating with foundation model providers (Anthropic, OpenAI, Gemini) and/or self-hosted inference, including prompt management, caching, and guardrails.
• Experience with vector stores, embeddings pipelines, and retrieval evaluation.
• Helpful to have experience with workflow tools like Argo or Dagster.

The Perks:

• A competitive salary, company bonus, health insurance, pension, wellbeing programme
• An exciting and dynamic role with career development opportunities and progression
• The opportunity to work with talented and diverse team in an inclusive work environment
• A learning culture where continued learning & development is supported and encouraged
• Remote working options and a flexible environment that promotes wellness and work life balance

Company Highlights:

• 20-30% YoY revenue growth since 2017
• Established global offices
• Top private equity sponsorship from Luminate Capital Partners
• 70,000+ regulations and standards on the platform
• A marketing leading retention rate over 95%

#CR