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Make Your Mark

We are looking for a deeply hands-on AI Engineer with proven expertise in Agentic AI and Generative AI systems. The ideal candidate has independently driven 3–4 end-to-end AI implementations — from requirements gathering and solution design through to production deployment — and is equally comfortable in writing production-grade code.

This role demands both breadth and depth: you will build and orchestrate intelligent agents, and embed robust governance frameworks that make those agents enterprise-ready.

You'll Get To

Key Responsibilities

• End-to-End AI Implementation
• Own 3–4 complete AI delivery cycles: discovery, requirements, solution design, build, test, and production deployment.
• Translate ambiguous business problems into concrete AI solutions with clear success metrics.
• Define and manage delivery milestones across cross-functional stakeholders.
• Conduct design reviews, code reviews, and production readiness assessments.
• Architecture & System Design
• Design multi-agent pipelines with clear separation of concerns, fault isolation, and observability.
• Define data flows, integration patterns (REST, gRPC, event-driven), and storage strategies for AI workloads.
• Present technical proposals to senior members -technical leads, Staff/Principal Engineers .
• Agentic AI – Build & Orchestration
• Design, build, and deploy intelligent agents for complex, multi-step reasoning and task execution.
• Implement agent orchestration using Google Workflows, Temporal, LangChain, LangGraph, CrewAI, or equivalent frameworks.
• Deploy agents on GCP (Vertex AI Agent Builder, Cloud Run, GKE) or AWS / Azure equivalents.
• Integrate agents with external tools, APIs, databases, and enterprise systems via function calling and tool-use patterns.
• Implement ReAct, Plan-and-Execute, and other advanced prompting and reasoning strategies.
• Agent Governance & Enterprise Readiness
• Design immutable, structured audit logs capturing agent decisions, tool invocations, and data accessed — enabling full traceability.Audit Trail:
• Implement content safety policies, permission scopes, and fine-grained access controls governing agent behaviour.Policies & Guardrails:
• Architect HITL checkpoints for high-risk decisions, escalation flows, and approval gates.Human-in-the-Loop (HITL):
• Design secure, reliable A2A protocols including message schemas, authentication, and failure handling.Agent-to-Agent (A2A) Communication:
• Establish agent identity frameworks (service accounts, OAuth, signed tokens) for secure system interactions.Agent Identity & Authentication:
• Build or adopt agent SDKs; maintain a centralised agent registry for discovery, versioning, and lifecycle management.Agent SDK & Registry:
• Define and instrument evaluation frameworks covering task success rate, latency, token cost, and output quality.Evaluation Metrics:
• Implement runtime monitoring for unexpected agent behaviour, runaway loops, and out-of-distribution outputs.Anomaly Detection:
• Develop risk scoring models to dynamically assess and throttle agent actions based on context and potential impact.Risk Scoring:
• Generative AI Engineering
• Design and implement RAG (Retrieval-Augmented Generation) pipelines with vector stores (Pinecone, Weaviate, pgvector, etc.).
• Fine-tune, prompt-engineer, and evaluate foundation models (Gemini, GPT-4, Claude, Llama) for domain-specific tasks.
• Optimise inference costs through caching, batching, model routing, and quantisation strategies.
• Build evaluation harnesses to benchmark model quality, factuality, and safety at scale.
  
  

Experience

Required Qualifications

• 5-6 years of software engineering experience, with at least 4 years focused on AI/ML systems.
• Demonstrated delivery of 3–4 full E2E AI projects (requirements → design → implementation → test → production).
• Proven experience designing and deploying complex, production-grade systems at scale.
  
  

Technical Skills

• Agentic AI: LangChain, LangGraph, CrewAI, AutoGen, Google Agent Development Kit (ADK), or similar.
• Cloud Platforms: GCP (Vertex AI, Cloud Run, GKE, Workflows) — AWS or Azure equivalents acceptable.
• Orchestration: Google Workflows, Apache Airflow, Prefect, or equivalent.
• LLM APIs: Gemini, OpenAI, Anthropic Claude, Mistral, or open-source models (Llama, Mistral).
• Vector DBs & RAG: Pinecone, Weaviate, Qdrant, pgvector, or Elasticsearch.
• Languages: Python (primary); Go, Java, C#, TypeScript a plus.
• Infra & DevOps: Docker, Kubernetes, Terraform, CI/CD pipelines (GitHub Actions, Cloud Build).
• Observability: OpenTelemetry, Prometheus, Grafana, or equivalent for AI workload monitoring.
• Security: OAuth 2.0, mTLS, IAM policies, secret management (Vault, Secret Manager).
  
  

Nice to Have

• Experience with Google Vertex AI Agent Builder or similar managed agent platforms.
• Contributions to open-source AI/agent frameworks.
• Familiarity with AI safety, responsible AI, and ethics frameworks.
• Experience with multi-modal models (vision, audio, code).
• Published research, conference talks, or technical blog posts on AI topics.
  
  

What You'll Bring

Thrive at BlackLine Because You Are Joining:

• A technology-based company with a sense of adventure and a vision for the future. Every door at BlackLine is open. Just bring your brains, your problem-solving skills, and be part of a winning team at the world's most trusted name in Finance Automation!
• A culture that is kind, open, and accepting. It's a place where people can embrace what makes them unique, and the mix of cultural backgrounds and varying interests cultivates diverse thought and perspectives.
• A culture where BlackLiner's continued growth and learning is empowered. BlackLine offers a wide variety of professional development seminars and inclusive affinity groups to celebrate and support our diversity.
  
  

BlackLine is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity or expression, race, ethnicity, age, religious creed, national origin, physical or mental disability, ancestry, color, marital status, sexual orientation, military or veteran status, status as a victim of domestic violence, sexual assault or stalking, medical condition, genetic information, or any other protected class or category recognized by applicable equal employment opportunity or other similar laws.

BlackLine recognizes that the ways we work and the workplace itself has shifted. We innovate in a workplace that optimizes a combination of virtual and in-person interactions to maximize collaboration and nurture our culture. Candidates who live within a reasonable commute to one of our offices will work in the office at least 3 days a week.

Accommodations

BlackLine is committed to creating an inclusive and accessible experience for all candidates. If you require a reasonable accommodation that would better enable your success during the application or interview process, please complete this form.

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