Who you are

• Proven Experience: 5+ years of professional experience in Applied AI Engineering, ML Engineering, or a closely related role with a strong focus on building and deploying AI-powered applications
• Applied AI & Python Expertise: Advanced proficiency in Python and hands-on experience building applications with leading AI/ML frameworks (e.g., LangChain, LlamaIndex, CrewAI, PyTorch). You are an expert with data and ML libraries (e.g., Pandas, spaCy)
• Production Generative AI Champion: Demonstrated success deploying and maintaining applications powered by LLMs and other generative models in a production environment
• Retrieval-Augmented Generation (RAG) Expertise: Deep, hands-on experience designing, building, and optimizing RAG pipelines. This includes expertise in vector databases (e.g., Qdrant, Pinecone, Weaviate), embedding strategies, and chunking techniques
• Agentic AI System Evaluation Expertise: Demonstrable experience with modern evaluation techniques for multi-step AI agents. You should be able to speak to the trade-offs of evaluating reasoning traces, tool usage, and final outcomes using frameworks like LangSmith, DeepEval, Ragas, TruLens, or custom-built solutions
• Prompt Engineering & In-Context Learning: Demonstrable skill in designing, testing, and optimizing complex prompts and few-shot examples to maximize model performance for specific tasks
• Fine-Tuning Proficiency: Experience in fine-tuning foundation models for specific downstream tasks, with a clear understanding of when to fine-tune versus when to use in-context learning or agentic approaches
• Scalable Model Serving: Advanced proficiency with API-driven frameworks for accessing and serving self-hosted foundation models (e.g., AWS SageMaker/Bedrock, Databricks Model Serving, TGI, vLLM), focusing on building resilient, scalable, and optimized integrations
• Performance and Cost Optimization: A proven ability to optimize AI systems for low latency and high throughput. You have experience with techniques like model quantization, caching strategies, and infrastructure choices to manage and reduce operational costs
• MLOps for AI Systems: Intermediate proficiency with MLOps tooling (e.g., MLFlow, Arize), and best practices for CI/CD, monitoring, and maintenance of complex AI systems
• Educational Foundation: Bachelor's Degree in Computer Science, Engineering, Statistics, or a related field (or equivalent practical experience). An advanced degree (Master's or Ph.D.) is a strong plus

What the job involves

• You’ll join a team where everyone, including you, is striving to constantly improve their knowledge of software development tools, practices, and processes. We are an incredibly supportive team. We swarm when problems arise and give excellent feedback to help each other grow. Working on our close-knit, multi-functional teams is a chance to share and grow your knowledge of different domains from databases to front ends to telephony and everything in between
• Working on our close-knit, multi-functional teams is a chance to share and grow your knowledge of different domains from databases to front ends to telephony and everything in between
• Are you passionate about harnessing the power of generative AI and foundation models to build truly intelligent products? At Invoca, we're a team of innovators committed to building exceptional teams and groundbreaking AI solutions.
• This is a unique opportunity to architect the next generation of AI-powered customer experiences, making a direct and measurable impact on our products and the success of our clients
• Architect and Deploy Applied AI Systems: Design, build, and deploy scalable, production-grade applications using foundation models and other advanced AI techniques to directly influence product performance and efficiency
• Engineer Advanced RAG and Agentic Systems: Go beyond basic implementation. Engineer robust Retrieval-Augmented Generation (RAG) pipelines and multi-step agentic workflows that can reason, use tools, and solve complex problems
• Contribute to Agentic AI System Evaluation: Establish and manage rigorous evaluation frameworks for complex AI agents. You will go beyond simple response quality to assess the entire agentic process, including the validity of reasoning steps, correctness of tool use, task completion rates, and overall robustness
• Excel in Prompt Engineering and Optimization: Craft, test, and manage sophisticated prompt chains and templates to ensure optimal performance, reliability, and cost-effectiveness from our AI models
• Build for Scale and Reliability: Develop resilient serving architectures that seamlessly integrate Large Language Models (LLMs) with enterprise systems, ensuring high availability and performance
• Champion MLOps for Applied AI: Develop and maintain sophisticated MLOps and CI/CD pipelines tailored for the unique challenges of generative AI, including prompt versioning, RAG pipeline management, and continuous evaluation of agent behavior
• Translate Business Needs into AI-Powered Solutions: Work as a strategic partner to product and engineering teams, deeply understanding customer challenges and translating them into innovative, viable, and impactful AI features

Benefits

• Paid Time Off - 20 days off for all full-time employees, plus 15 paid holidays, 10 days compassionate leave, 3 days volunteer time and more
• Medical, Dental and Vision Coverage
• Mental Well-being & Employee Assistance Program
• Paid Family/Medical Leave - up to six weeks 100% paid leave for baby bonding, adoption, and caring for family members, and up to twelve weeks 100% paid leave for one’s own medical leave
• Invacation (Sabbatical) - an additional week of PTO along with a bonus after seven years of service
• Wellness Subsidy - for gym membership, fitness classes, etc.