Senior AI Engineer
- Роль
- AI / ML
- Опыт
- Синьор
- Занятость
- Полная занятость
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Коротко по делу
Senior AI Engineer with strong hands-on experience in Generative AI and Agentic AI within the Microsoft Azure ecosystem. Must have production-ready AI application development experience using Azure AI Foundry, agentic workflows, RAG, knowledge graphs, embeddings, and retrieval techniques. Requires strong software engineering skills, ideally with Python, and experience integrating LLM applications with APIs and data sources.
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Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients.
We are looking for a Senior AI Engineer with strong hands-on experience designing and building Generative AI and Agentic AI solutions within the Microsoft Azure ecosystem. This is a highly technical role focused on building production-ready AI applications using Azure AI Foundry, Microsoft Fabric, agentic workflows, RAG, knowledge graphs, embeddings, and modern retrieval techniques. The ideal candidate combines strong software engineering skills with practical experience building and evaluating LLM-powered applications. Experience in financial services is a plus, but not required. Key Responsibilities Design, build, and deploy production-ready Generative AI and Agentic AI applications using Azure AI Foundry. Develop agentic workflows using agents, tools, skills, orchestration patterns, and enterprise data sources. Build and optimize RAG architectures, including retrieval, grounding, context management, chunking, embeddings, and vector search. Design and implement graph-based approaches and knowledge graphs to enhance retrieval and reasoning. Work extensively with Microsoft Fabric and Azure data services to connect AI applications with enterprise data. Develop and integrate AI agents, skills, tools, and APIs to support complex business workflows. Implement LLM and agent evaluation frameworks (evals) to measure quality, accuracy, relevance, reliability, and performance. Experiment with different models, prompts, retrieval strategies, chunking approaches, and agent architectures. Build reusable components and patterns for AI application development. Collaborate with Data Scientists, Data Engineers, Software Engineers, and business stakeholders to translate use cases into scalable AI solutions. Troubleshoot and optimize AI applications across development and production environments. Contribute to architecture decisions, technical documentation, and engineering best practices.
Strong hands-on experience with Azure AI Foundry — required. Hands-on experience building Agentic AI / agent-based workflows — required. Strong practical experience with RAG architectures — required. Experience with graphs or knowledge graph approaches — required. Strong understanding and hands-on experience with chunking and embedding strategies — required. Experience building and working with AI agents, tools, and skills — required. Experience with LLM / AI evaluation (evals) — required. Experience working with Microsoft Fabric or comparable Azure data platforms — strongly preferred. Strong software engineering skills, ideally with Python. Experience integrating LLM applications with APIs, enterprise systems, and data sources. Experience taking AI prototypes into production. Strong understanding of LLM application architecture and modern Generative AI patterns. Nice to Have Experience in financial services, banking, lending, insurance, or related industries. Experience with Azure-native data and AI services. Experience with AI observability, governance, and responsible AI. Experience with CI/CD and cloud-native application development. Experience with multi-agent architectures. Experience with semantic search and vector databases.
Our perks and benefits: 📚 Learning Opportunities: Certifications in AWS (we are AWS Partners), Databricks, and Snowflake. Access to AI learning paths to stay up to date with the latest technologies. Study plans, courses, and additional certifications tailored to your role. Access to Udemy Business, offering thousands of courses to boost your technical and soft skills. English lessons to support your professional communication. 👨🏽💻 Travel opportunities to attend industry conferences and meet clients. 👩🏫 Mentoring and Development: Career development plans and mentorship programs to help shape your path. 🎁 Celebrations & Support: Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones. Company-provided equipment. ⚖️ Flexible working options to help you strike the right balance. Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.
Чем предстоит заниматься
- Design, build, and deploy production-ready Generative AI and Agentic AI applications using Azure AI Foundry.
- Develop agentic workflows using agents, tools, skills, orchestration patterns, and enterprise data sources.
- Build and optimize RAG architectures, including retrieval, grounding, context management, chunking, embeddings, and vector search.
- Design and implement graph-based approaches and knowledge graphs to enhance retrieval and reasoning.
- Work extensively with Microsoft Fabric and Azure data services to connect AI applications with enterprise data.
- Develop and integrate AI agents, skills, tools, and APIs to support complex business workflows.
- Implement LLM and agent evaluation frameworks (evals) to measure quality, accuracy, relevance, reliability, and performance.
- Experiment with different models, prompts, retrieval strategies, chunking approaches, and agent architectures.
- Build reusable components and patterns for AI application development.
- Collaborate with Data Scientists, Data Engineers, Software Engineers, and business stakeholders to translate use cases into scalable AI solutions.
- Troubleshoot and optimize AI applications across development and production environments.
- Contribute to architecture decisions, technical documentation, and engineering best practices.
- Design, build, and deploy AI-powered applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and intelligent agents for financial use cases.
- Develop AI workflows capable of analyzing multidimensional financial data and generating automated financial insights and recommendations.
- Build integrations between AI solutions and enterprise planning platforms such as Workday Adaptive Planning, CaptivateIQ, or Anaplan.
- Develop automation pipelines that perform variance analysis, financial forecasting, and narrative generation for monthly and quarterly reporting.
- Translate complex business requirements from Finance, FP&A, and Revenue Operations teams into scalable Python- and SQL-based solutions.
- Design semantic layers and AI workflows that support financial planning, incentive compensation, and operational reporting.
- Collaborate with Finance Directors and executive stakeholders to understand business needs and deliver AI-driven solutions.
- Ensure AI solutions comply with corporate governance, security standards, data access policies, and SOC2 requirements.
- Optimize prompt engineering strategies and AI model performance to maximize accuracy and business value.
- Continuously evaluate emerging AI technologies and recommend improvements to financial automation capabilities.
Что требуется
- Strong hands-on experience with Azure AI Foundry — required.
- Hands-on experience building Agentic AI / agent-based workflows — required.
- Strong practical experience with RAG architectures — required.
- Experience with graphs or knowledge graph approaches — required.
- Strong understanding and hands-on experience with chunking and embedding strategies — required.
- Experience building and working with AI agents, tools, and skills — required.
- Experience with LLM / AI evaluation (evals) — required.
- Experience working with Microsoft Fabric or comparable Azure data platforms — strongly preferred.
- Strong software engineering skills, ideally with Python.
- Experience integrating LLM applications with APIs, enterprise systems, and data sources.
- Experience taking AI prototypes into production.
- Strong understanding of LLM application architecture and modern Generative AI patterns.
- Experience in financial services is a plus, but not required.
- 4+ years of experience in software engineering, AI engineering, data engineering, or related technical roles.
- At least 2 years of hands-on experience building AI or Machine Learning applications.
- Proven experience working with Corporate Finance, FP&A, Accounting, Revenue Operations, or similar business functions.
- Deep understanding of SaaS financial metrics including ARR, NRR, deferred revenue, budgeting, forecasting, and incentive compensation.
- Knowledge of GAAP principles and three-statement financial modeling.
- Experience integrating enterprise planning platforms such as: Workday Adaptive Planning CaptivateIQ Anaplan
- Ability to communicate technical concepts effectively to executive and non-technical stakeholders.
- Strong analytical thinking and problem-solving skills.
- Experience working in remote and cross-functional teams.
- At least 4 years of professional experience building and deploying AI, ML, or software solutions in production environments.
- Experience in financial services, banking, lending, insurance, or related industries.
- Experience with Azure-native data and AI services.
- Experience with AI observability, governance, and responsible AI.
- Experience with CI/CD and cloud-native application development.
- Experience with multi-agent architectures.
- Experience with semantic search and vector databases.
Преимущества
- 📚 Learning Opportunities: Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
- Access to AI learning paths to stay up to date with the latest technologies.
- Study plans, courses, and additional certifications tailored to your role.
- Access to Udemy Business, offering thousands of courses to boost your technical and soft skills.
- English lessons to support your professional communication.
- 👨🏽💻 Travel opportunities to attend industry conferences and meet clients.
- 👩🏫 Mentoring and Development: Career development plans and mentorship programs to help shape your path.
- 🎁 Celebrations & Support: Special day rewards to celebrate birthdays, work anniversaries, and other personal milestones.
- Company-provided equipment.
- ⚖️ Flexible working options to help you strike the right balance.
- Other benefits may vary according to your location in LATAM. For detailed information regarding the benefits applicable to your specific location, please consult with one of our recruiters.
- Every day lunches! (headquarters): Vegetarian, vegan, gluten and sugar free options. Gourmet meals every Friday with our on-site chef!
- Flexible working options to help you strike the right balance.
- All the equipment you need to harness your talent (Macbook and accessories).
- Snacks and beverages available everyday (headquarters).
- After office events, football, tennis and game nights (headquarters).
- Everyone is welcome to join our football league every Wednesday’s and Friday’s. Challenge your teammates to a pool game and win the office’s trophy! Tennis courts available for friendly matches. Not a sports person? Don’t worry, we also have chess championships, game and music nights for you to join!
- Learning opportunities: AWS Certifications (we are AWS Partners). Study plans, courses and other certifications. English Lessons. Learn from your teammates on our Tech Tuesdays!
- Mentoring and Development opportunities to shape your career path.
- Anniversary and birthday gifts.
- Great location and even greater teammates!
- Certifications in AWS (we are AWS Partners), Databricks, and Snowflake.
- Travel opportunities to attend industry conferences and meet clients.
- Career development plans and mentorship programs to help shape your path.
- Special day rewards to celebrate birthdays, work annivers anniversaries, and other personal milestones.
- Other benefits may vary according to your location in LATAM.
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Что говорят о компании
3.8/ 5