Senior AI Engineer

Summary

Join InVitro Capital, a venture studio building and scaling transformative companies, as a Senior AI Engineer. You will design and implement AI-driven systems, optimize model strategies, engineer AI agents, and enhance model accuracy. Collaborate with clients, integrate language models, and deploy applications in cloud environments. Contribute to data preparation and identify process optimizations. This role requires a Bachelor's degree, 6+ years of AI solution engineering experience, and expertise in AI agents, machine learning, data engineering, and cloud deployment.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or a related field
• 6+ years in AI solution engineering with a strong focus on process automation and client-facing collaboration
• Demonstrated experience in designing, building, testing, and deploying AI agents using frameworks such as Crew AI, Windsurf, LangChain, Rasa, or equivalent toolkits
• Proficient in using and integrating AI tools like ChatGPT, OCR technologies, and workflow automation frameworks
• Proven experience in model development, transfer learning, ensemble methods, and online learning strategies. Familiarity with MLOps practices for model monitoring and retraining workflows
• Proficiency in data preprocessing, handling structured and unstructured data, and managing ETL pipelines for AI applications
• Hands-on experience deploying AI applications on Azure or AWS, with a strong understanding of cloud-native services and scalability best practices
• Familiarity with CI/CD pipelines, version control systems, and infrastructure-as-code tools to support seamless deployment of AI solutions
• Demonstrated ability to analyze complex business or technical processes and develop impactful AI-driven solutions
• Strong interpersonal and written communication skills, capable of explaining technical solutions to non-technical stakeholders

Responsibilities

• Design and implement AI-driven systems, including automating workflows such as data scraping, OCR scanning, PDF processing, and care plan generation
• Evaluate and apply the best-fit model strategies—training from scratch, fine-tuning pre-trained models, leveraging ensemble learning, or using cloud-based LLMs (e.g., GPT, Claude, Gemini)
• Design, implement, and test AI agents capable of task automation, decision support, and multi-step reasoning using tools such as LangChain, Rasa, Crew AI, and Windsurf
• Improve models through online learning, user feedback loops, and retraining pipelines based on real-world outcomes
• Work directly with stakeholders to gather requirements, propose AI solutions, and communicate technical strategies clearly
• Use advanced tools like ChatGPT, Claude, and open-source LLMs to build smart assistants, workflows, and agents that solve real-world problems
• Deploy AI applications in cloud environments (AWS, Azure, or GCP) with a focus on scalability, performance, and production readiness
• Clean and curate datasets for AI consumption, focusing on enhancing quality, structure, and annotation standards
• Continuously identify bottlenecks and propose AI-powered optimizations to improve processes and reduce manual workloads
• Architect and optimize agentic pipelines using tools like Crew AI or LangGraph, integrating reasoning chains and tool-use

Preferred Qualifications

Passion for staying updated on emerging AI trends, with a proactive attitude toward proposing and implementing creative solutions to enhance efficiency and drive

Benefits

Competitive compensation: We offer a competitive compensation package, with salaries ranging from [$5,000 to $9,100 monthly], payable in USD