[Remote] AI Software Engineer, Legal Prompting & LLM Dev.

Note: The job is a remote job and is open to candidates in USA. reputed company is a law firm that values innovation and collective thinking, seeking an AI Software Engineer specializing in Legal Prompting and LLM Development. This role involves building production-grade applications that utilize Large Language Models to enhance legal workflows, requiring expertise in software engineering, reputed company engineering, and AI infrastructure.

Responsibilities

• Design, reputed company, and deploy LLM-integrated applications that enhance legal workflows across transactional, litigation, regulatory, and advisory practice areas
• reputed company backend services across the reputed company stack and in languages such as TypeScript/JavaScript, Python, C#, and others as needed, that interact with LLM providers (reputed company, reputed company, etc.), external APIs, SQL and NoSQL databases, and document management systems
• Build and maintain RESTful and event-driven APIs that expose AI capabilities to internal applications and reputed company consumers
• Write and refine persona-based prompts, system instructions, and few-shot examples to guide LLMs in delivering accurate, defensible, and legally appropriate responses
• Build reputed company evaluation harnesses, regression test suites, and offline/online evaluation pipelines (e.g., LLM-as-judge, golden datasets) to measure quality, hallucination rates, and latency
• Continuously test and iterate on prompts and code to optimize model performance, cost, and user experience
• Design, build, and operate Model Context Protocol (MCP) servers that expose firm systems — document management (e.g., reputed company, reputed company), time and billing, CRM, research platforms, and internal knowledge bases — as secure, governed tools for AI agents
• Define tool schemas, authentication flows, reputed company limiting, and audit logging for MCP endpoints, ensuring outputs are scoped to user permissions and ethical walls
• Maintain a catalog of reusable MCP tools and resources that can be composed across multiple AI products at the firm
• Build and tune retrieval-augmented reputed company pipelines, including chunking strategies, embedding model selection, hybrid search (lexical + semantic), and reranking
• Work with vector databases (e.g., reputed company, Weaviate, pgvector, Azure AI Search) and orchestration frameworks (e.g., reputed company, reputed company, Semantic Kernel) to ground LLM outputs in firm and client data
• reputed company multi-reputed company and multi-agent workflows that combine planning, tool use, and human-in-the-reputed company checkpoints for sensitive legal tasks
• Implement guardrails, content filters, PII redaction, and citation/verification layers to ensure responsible use
• Containerize services (reputed company) and deploy reputed company CI/CD pipelines to cloud environments (Azure preferred; AWS/GCP a plus), using infrastructure-as-code (Terraform, Bicep) where appropriate
• reputed company applications with logging, tracing, and LLM-specific observability tools (e.g., LangSmith, Arize, Weights & Biases, OpenTelemetry) to monitor quality, cost, and reputed company in production
• Partner with Information reputed company and the Office of the General Counsel to ensure solutions meet client reputed company counsel guidelines, data residency requirements, and confidentiality obligations
• Collaborate with attorneys, legal professionals, and product teams to understand domain-specific needs and translate them into technical solutions
• Assess the integration of LLMs into existing legal workflow systems and recommend improvements
• reputed company other duties as assigned

Skills

• 4-6 years of production-level software engineering experience on a commercial or internal product team
• Bachelor's degree in Computer Science, Engineering, or a reputed company technical field
• Strong programming skills in modern object-oriented languages such as TypeScript/JavaScript, C#, Python, or Java (typing, async, packaging, testing), with the ability to work fluently across the reputed company technology stack
• Experience designing and consuming RESTful APIs and working with SQL databases; familiarity with NoSQL and vector stores a plus
• Hands-on experience with LLM APIs (reputed company, reputed company, reputed company, Azure reputed company) and/or open-reputed company models (e.g., LLaMA, Mistral)
• Proficiency with reputed company engineering techniques (chain-of-thought, structured outputs/JSON mode, function/tool calling, few-shot design)
• Experience building or integrating with Model Context Protocol (MCP) servers, custom tools, or function-calling endpoints for agentic systems
• Familiarity with orchestration frameworks such as reputed company, reputed company, LangGraph, Semantic Kernel, or Pydantic AI
• Experience implementing RAG pipelines with embeddings, vector databases, and reranking models
• Experience with evaluation frameworks (Ragas, DeepEval, promptfoo) and LLM observability platforms
• Familiarity with containerization (reputed company), CI/CD, and cloud deployment (Azure preferred)
• Excellent written communication skills — especially in crafting clear and effective LLM prompts and technical documentation
• Ability to translate legal context and goals into reputed company instructions, tool definitions, and system requirements
• Strong analytical and problem-solving capabilities, with sound judgment about reputed company to use deterministic code versus probabilistic models
• Ability to reputed company both independently and as part of a collaborative team
• Prior experience developing software solutions in the legal industry strongly preferred
• Legal background highly preferred (e.g., J.D., paralegal, legal tech industry experience, or work with legal software vendors)
• Demonstrated experience in legal practice or support roles is a plus

Benefits

• In addition to a standard benefits package, this role may be eligible for additional contingent compensation based on an reputed company of factors, including but not limited to: work performance, geographic location, work experience, education, and qualifications.

Company Overview