Main tasks & responsibilities
- Work directly with customers to understand their business challenges, technical requirements, and operational workflows.
- Design, develop, and deploy AI-powered solutions tailored to real-world customer needs.
- Build production-ready applications, APIs, integrations, and automated workflows using modern software engineering practices.
- Develop and integrate LLM-based applications, AI agents, and intelligent automation systems.
- Own the end-to-end technical delivery process, from requirements gathering and prototyping to deployment and ongoing optimization.
- Integrate solutions with customer infrastructure, databases, third-party APIs, and enterprise systems.
- Troubleshoot complex technical issues, ensuring reliability, scalability, security, and performance.
- Collaborate closely with product and engineering teams to translate customer feedback into product improvements and reusable capabilities.
- Identify opportunities to automate processes, improve operational efficiency, and deliver measurable business value.
- Act as a trusted technical partner, communicating effectively with both technical and non-technical stakeholders.
Requirements
- Bachelor's or Master's degree in Computer Science, Software Engineering, or a related technical field, or equivalent practical experience.
- 3+ years of professional experience in software engineering, backend development, or similar technical roles.
- Strong programming skills in Python and/or TypeScript.
- Solid experience designing and developing REST APIs, backend services, and scalable software applications.
- Hands-on experience with cloud platforms such as AWS, Azure, or GCP.
- Experience working with relational and/or NoSQL databases, data pipelines, and third-party integrations.
- Understanding of LLMs, generative AI technologies, and AI application development.
- Familiarity with software deployment, CI/CD practices, containerization, and production environments.
- Strong analytical thinking, debugging skills, and ability to solve complex technical problems independently.
- Excellent communication skills and ability to translate business needs into technical solutions.
- Comfortable working directly with customers in fast-paced, dynamic, and ambiguous environments.
- Strong sense of ownership, autonomy, and results-oriented mindset.
Nice to have
- Hands-on experience building AI agents, RAG pipelines, and LLM-powered applications.
- Experience with AI frameworks such as LangChain, LangGraph, LlamaIndex, or similar.
- Familiarity with vector databases, embeddings, and semantic search technologies.
- Experience with Docker, Kubernetes, Terraform, or infrastructure-as-code tools.
- Knowledge of enterprise security, authentication protocols, and data privacy best practices.
- Experience integrating with enterprise platforms such as Salesforce, SAP, or other business-critical systems.
- Previous experience in a Forward-Deployed Engineer, Solutions Engineer, or customer-facing engineering role.
- Experience working in early-stage startups or high-growth technology companies.
- Familiarity with monitoring, observability, and evaluation frameworks for AI applications.
- Strong product mindset and ability to identify opportunities for scalable, reusable solutions.