• Ship AI tools that move function KPIs • Build and ship internal AI tools and automations • Define a named owner function for each shipped tool • Establish eval harnesses and monitoring • Operate as a force multiplier through AI agents • Maintain and continuously upgrade a personal AI-engineering setup • Architect the AI platform layer for Tango • Drive shared AI architecture decisions across teams • Track frontier-model capability • Embed across function clusters to land AI in real workflows

Role Description The AI Engineer builds the retrieval, evaluation, and workflow plumbing that makes Lena reliable. You'll work alongside the Senior AI Engineer on the reasoning layer, and across the team on integration into the broader platform. - Building and tuning RAG components: chunking strategy, retrieval scoring, prompt scaffolding, grounding heuristics. - Wiring evaluation harnesses that catch regressions on every release. - Working on the Python services that mediate between Lena and the rest of the platform. - Working with backend (.NET) and frontend (React) engineers to land AI-affecting changes safely. Qualifications - 1+ years of software / ML engineering experience. - Advanced in Python. - Shipped Python code that real users relied on (production or internal stakeholders). - Hands-on experience with LLMs, RAG, or AI workflows beyond tutorials. - Comfortable with REST APIs and JSON-based integrations. Requirements - 1–3 years of software engineering, ML engineering, or applied AI experience. - Hands-on exposure to LLMs, RAG systems, or AI workflows beyond tutorials or coursework. - Strong Python fundamentals; you have shipped Python that other people relied on. - Comfort with REST APIs, JSON structures, and modern SaaS systems. - Familiarity with prompt engineering and modern AI tooling. Benefits - Flexible / unlimited time off. - Health insurance. - Equity participation, discussed at offer. - Fully remote. - Architectural ownership of work that ships to real enterprise customers. - Direct working relationships with the people setting platform strategy. - A growth-stage platform where the decisions you make in your first year shape the product for years. - AI-assisted tooling licensed by NetSpeek (Cursor, Claude Code, GitHub Copilot, or comparable).

Title: AI Engineer [Trading Analytics & Data Engineering] Location: Houston, TX Department: PTS - SHELL Job Description: Join the ECI Group's Professional Technical Services Network as an AI Engineer [Trading Analytics & Data Engineering]. This is a Houston based contract role with an anticipated May 5, 2026 start date and ending on December 31, 2026. Note: You must be a US Citizen or Permanent US Resident to qualify for this position. About the role We're hiring an AI Engineer with a strong data engineering foundation and excellent communication skills—ideally with commodity or financial trading experience. You'll partner with traders and trading analysts to rapidly build AI powered analytics over market pricing and fundamentals data, using Databricks and Spark to deliver value at speed. What you'll do: - Design and ship AI driven analytics for front office use (seasonality, correlation, regression, forecasting, scenario modelling). - Build reusable and scalable data pipelines in Databricks (PySpark/Spark, Delta/Unity Catalog), optimizing cost, reliability, and performance. - Run statistical/econometric analyses on large datasets (e.g., market & fundamental time series data). - Collaborate directly with traders/analysts—translate ambiguous questions into shippable solutions; communicate insights clearly. - Implement LLM/agentic workflows: prompt engineering, LangGraph orchestration, MCP integrations, tool calling, retrieval, and guardrails. - Productionize solutions with testing, observability, versioning, and documentation. What you'll bring: - Hands on Databricks + Spark expertise (PySpark, SQL, Delta, Unity Catalog). - Proven data engineering skills (ingestion, modelling, orchestration, performance tuning). - Strong statistics/economics/data science fundamentals formarket time series. - Experience building LLM solutions (prompting, retrieval, agent flows; LangGraph, MCP) and integrating with trading data/services. - Experience with CI/CD, Terraform, MLflow/feature stores, vector DBs, and governance (PII handling, data lineage). - Excellent stakeholder skills; able to work on desk with traders/analysts and deliver fast. Nice to have: - Background in commodity or financial trading. - Familiarity with market microstructure, supply demand fundamentals, risk management. Ways of working - Hybrid; high touch collaboration with trading teams. - Bias to prototype fast, iterate with users, and harden to production. - Maintain operational stability of production pipelines using secure, modern CI/CD engineering practices — with automated testing, quality gates, and built in reliability across development, security, and operations. Please Note: The ECI Group uses AI-assisted tools in the early stages of application review, with all decisions guided by human oversight and fully compliant with General Data Protection Regulation (GDPR) and ECI Group's applicable data protection policies and Privacy Notice.

About HuzzleAt Huzzle, we connect exceptional talents with top opportunities at leading companies across the UK, US, Canada, Europe, and Australia. Our clients include startups, digital agencies, and tech platforms in industries such as SaaS, MarTech, FinTech, and AI. Unlike an outsourcing agency, we place you directly with a client where you’re hired in-house as a valued member of their team. **Role Type: Full-time** **Engagement: Independent Contractor** Job SummaryWe are seeking a skilled and innovative **Remote AI Engineer** with experience in machine learning, large language models (LLMs), and AI application development. You will work closely with product managers, software engineers, and data teams to design intelligent systems, develop AI-powered features, and improve model performance across various applications. This is an exciting opportunity for someone passionate about artificial intelligence, automation, and scalable software development. Key Responsibilities - Design, develop, and deploy AI and machine learning models for production environments. - Build AI-powered applications using LLMs such as GPT, Claude, Gemini, or open-source models. - Create and optimize prompt engineering workflows for generative AI applications. - Develop APIs and backend systems that integrate AI services into web and mobile applications. - Fine-tune models and improve inference performance, latency, and scalability. - Work with structured and unstructured datasets for model training and evaluation. - Collaborate with cross-functional teams to translate business needs into AI solutions. - Implement vector databases, embeddings, and retrieval-augmented generation (RAG) pipelines. - Monitor AI system performance and continuously improve reliability and accuracy. - Stay updated with the latest advancements in AI, machine learning, and automation technologies.