• Design and develop scalable data pipelines, backend services, and APIs. • Build knowledge graph solutions, including graph data modeling, relationship mapping, and graph traversal logic. • Build ETL pipelines. • Design data models. • Implement GraphRAG solutions combining knowledge graphs, vector search, metadata, and LLM-based retrieval. • Create Source to Target Mappings (STMs) for ETL specifications. • Implement automated ingestion patterns, incremental (delta) updates, and streaming/CDC workflows. • Gather requirements, set targets, define interface specifications, and conduct design sessions. • Work closely with data consumers to ensure proper integration. • Adapt and learn in a fast-paced project environment.

Role Description Avalara is looking for an AI Automation Engineer to help build an enterprise-grade automation ecosystem that improves how work is automated, orchestrated, governed, and scaled across the company. In this high-impact individual contributor role, you will use n8n as a core platform to design secure, reliable, and measurable automation solutions that reduce manual work, improve process quality, and support faster business transformation. You will work across functions to embed artificial intelligence-enabled workflows, intelligent decisioning, reusable automation patterns, and observability into enterprise processes. You will help Avalara raise its automation standards by building practical solutions, mentoring others, and improving how teams use artificial intelligence to increase productivity, quality, and operational scale. You will report to Sr Director, IT Support. Responsibilities - Engineer scalable, secure, and resilient automation solutions using n8n and related integration platforms. - Design hybrid automation patterns using n8n, Boomi, application programming interfaces, event-driven systems, and artificial intelligence agents. - Build artificial intelligence-enabled workflows that support intelligent decisioning, human-in-the-loop controls, prompt management, and model integrations. - Define development standards, reusable templates, exception handling, retry strategies, approval patterns, and security protocols for enterprise automation. - Implement environment strategies, continuous integration and continuous delivery pipelines, versioning, and governance models for automation workflows. - Establish logging, monitoring, reliability guardrails, anomaly detection, and alerting to improve uptime, workflow trust, and recovery time. - Define responsible artificial intelligence governance for model selection, cost controls, prompt and version management, data privacy, and auditability. - Lead technical design sessions, workflow reviews, architecture reviews, and post-incident reviews. - Mentor engineers, contractors, and implementation teams on automation design, artificial intelligence agents, prompt engineering, and responsible automation practices. - Use metrics such as adoption, cycle-time reduction, service levels, recovery time, cost per workflow, and business impact to guide improvement. Qualifications - Bachelor's degree in Computer Science Engineering. - 10+ years of experience in enterprise automation, workflow engineering, integration engineering, or platform architecture. - Deep hands-on experience with n8n or Boomi, including building cross-functional automations, artificial intelligence-enabled workflows, agents, and orchestration patterns. - Experience designing application programming interface-first and event-driven architectures, including REST, webhooks, OAuth, JSON Web Tokens, application programming interface security, and secure integration of artificial intelligence services. - Experience with cloud platforms such as Amazon Web Services, Microsoft Azure, or Google Cloud Platform, including artificial intelligence or machine learning services such as Amazon Bedrock or Azure OpenAI. - Applied experience using large language models, prompt engineering, artificial intelligence agents, observability, monitoring, and automation metrics to improve productivity, reliability, quality, scale, cost, or cycle time. Benefits - Total Rewards: In addition to a great compensation package, paid time off, and paid parental leave, many Avalara employees are eligible for bonuses. - Health & Wellness: Benefits vary by location but generally include private medical, life, and disability insurance. - Inclusive culture and diversity: Avalara strongly supports diversity, equity, and inclusion, and is committed to integrating them into our business practices and our organizational culture. We also have a total of 8 employee-run resource groups, each with senior leadership and exec sponsorship. Company Description Avalara is an AI-first Company. AI is embedded in our workflows, decision-making, and products. Success here requires embracing AI as an essential capability. You’ll bring experience using AI and AI-related technologies, ready to thrive here. You’ll apply AI every day to business challenges - improving efficiency, contributing solutions, and driving results for your team, our company, and our customers. You’ll grow with AI by staying curious about new trends and best practices, and by sharing what you learn so others can benefit too. We’re defining the relationship between tax and tech. We’ve already built an industry-leading cloud compliance platform, processing over 54 billion customer API calls and over 6.6 million tax returns a year. Our growth is real - we're a billion dollar business - and we’re not slowing down until we’ve achieved our mission - to be part of every transaction in the world. We’re bright, innovative, and disruptive, like the orange we love to wear. It captures our quirky spirit and optimistic mindset. It shows off the culture we’ve designed, that empowers our people to win. We’ve been different from day one. Join us, and your career will be too. We’re An Equal Opportunity Employer. Supporting diversity and inclusion is a cornerstone of our company — we don’t want people to fit into our culture, but to enrich it. All qualified candidates will receive consideration for employment without regard to race, color, creed, religion, age, gender, national orientation, disability, sexual orientation, US Veteran status, or any other factor protected by law. If you require any reasonable adjustments during the recruitment process, please let us know.

• Phase 1 build of the AI orchestrator — intent & slot extraction, policy engine, planner, composer LLM, output guardrails, PII redaction. • Basic RAG for motor policy Q&A. • Authenticated claim-status lookup. • Prompt engineering.

Role Description We are developing Ask Seeking Alpha — a high-load financial analysis system based on Large Language Models. The architecture is built on complex multi-agent orchestration using LangGraph, FastAPI, and Elasticsearch. We are looking for a Senior Python AI Engineer specialized in Generative AI to: - Design agent workflows - Optimize interactions with models (OpenAI, AWS Bedrock) - Ensure the reliability of non-deterministic systems in production Tech Stack: - Python (Asyncio) - FastAPI - LangChain - LangGraph - Pydantic - Elasticsearch - AWS Bedrock / OpenAI API - LangSmith Qualifications - Strong proficiency in modern Python - Deep understanding of asynchronous programming (asyncio) patterns - Experience with FastAPI and Pydantic (v2) - Production experience with LangChain - Hands-on experience or deep conceptual understanding of LangGraph (or similar state-machine based agent frameworks) - Strategies for handling LLM hallucinations and ensuring reliable outputs - Experience forcing LLMs to adhere to strict schemas (Pydantic/JSON mode) - Advanced strategies for managing limited context windows - Understanding the trade-offs between model size, latency, and cost Requirements - Reduce end-to-end latency through asynchronous processing and streaming (SSE) - Implement semantic caching strategies to minimize API costs and response time - Optimize token usage without sacrificing answer quality - Implement automated evaluation pipelines using LangSmith - Set up regression testing for prompts and agents to measure quality (correctness, faithfulness) before deployment - Refine retrieval strategies - Work on hybrid search implementation (Keyword + Vector), re-ranking, and query expansion Nice to Have - Experience with Elasticsearch (DSL queries, analyzers) - Knowledge of vector databases and embedding models - Background in FinTech or familiarity with financial data structures