Manage teams designing AI workflows at Magical, improving processes and customer solutions through innovative technology. Collaborate closely with engineering for high - stakes integrations and feedback - based enhancements.
About the role
- Senior AI Engineer developing and launching AI products for Valsoft Corporation. Collaborating on AI initiative across portfolio companies with hands-on software engineering tasks.
Responsibilities
- Drive the development and launch of new AI-powered products — from concept and prototype to market-ready release — with a focus on rapid iteration and measurable impact.
- Operate with a startup mindset: bias toward action, ownership across the full stack, and the ability to turn ambiguity into execution.
- Build scalable systems that not only attract new customers but also deepen adoption and upsell opportunities across our existing base.
- Build RESTful APIs, microservices, front and back-end components using a polyglot approach (Python, JavaScript frameworks)
- Develop context strategies (e.g., embeddings, retrieval augmentation, windowing) for reliability, security, and cost efficiency
- Apply evaluation frameworks (Promptfoo, OpenAI Evals, LangSmith) to systematically test, compare, and validate LLM outputs
- Build and tune AI models, assistants, agentic workflows, vector databases.
- Work closely with senior engineers and product owners to clarify requirements and deliver solutions that add measurable business value
- Work closely with other teams to design interfaces and get them implemented for consumption by AI tooling and products.
- Mentor engineers on prompt design, evaluation best practices, and context strategies
- Participate in sprint planning, code reviews, and backlog grooming.
- Integrate regression and adversarial testing into CI/CD pipelines to prevent prompt drift
- Define automated evaluation suites for LLM applications (truthfulness, consistency, compliance)
- Support efforts to reduce technical debt and improve maintainability.
- Experiment with and apply Generative AI and ML tools where they can accelerate development or improve user experience
- Create, optimize, and manage complex prompt strategies to maximize AI model performance
- Develop reusable prompt templates for consistent outputs across multiple use cases
- Design and optimize NLQ interfaces that let users query enterprise data (SQL/NoSQL, APIs, vector stores) in natural language, applying context engineering and evaluation frameworks to ensure accuracy, security, and business relevance.
- Troubleshoot and optimize performance, scalability, and data-handling issues
- Adapt to different technical environments across the portfolio.
Requirements
- 5–8 years of professional software engineering experience with Python and JavaScript frameworks
- Hands-on expertise with Generative AI and ML tools (Promptfoo, OpenAI Evals, LangSmith, LangChain, AWS Bedrock, Azure AI, etc.) is a must
- Familiarity with vector databases (e.g., PostgreSQL/pgvector, Pinecone, Weaviate, Milvus) and RAG (Retrieval-Augmented Generation) pipelines is preferred
- Deep and recent experience with Generative AI or machine learning development tools (Claude Code, Github Copilot, AWS Bedrock, OpenAI, LangChain, Azure AI, etc.) is preferred
- Proven ability to design and implement NLQ solutions enabling users to query structured/unstructured data sources conversationally, with focus on accuracy, performance, and security.
- Familiarity with Git-based workflows and CI/CD pipelines.
- Collaborative mindset with strong communication skills
- Comfortable working in a remote, distributed environment
- Willingness to learn, experiment, and take initiative.
Benefits
- Competitive compensation package
- Performance-based bonus potential
- Comprehensive benefits package.
- Hybrid or Fully remote work environment
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