Senior Software Engineer (Applied AI)

Requirements

• Ideal candidates bring curiosity, a love for solving ambiguous problems, and hands-on experience applying LLMs in production
• 6+ years of software engineering experience, with at least 2 years working directly on AI/ML-powered applications
• Strong fluency in AI tooling (e.g. OpenAI APIs, Anthropic APIs)
• Strong proficiency with modern backend languages (Python, Go, or similar)
• Practical understanding of LLMs, prompt engineering and agentic architectures
• High degree of ownership and comfort in experimental, fast-moving environments
• Ability to take complete ownership of AI solutioning end-to-end starting from gathering requirements from stakeholders to deploying solutions in production
• (Desirable) Exposure to customer-facing roles or user research for AI product development
• (Desirable) Familiarity with retrieval techniques (e.g., vector databases, RAG)
• (Desirable) Excellent problem-solving, communication, and teamwork skills, with the ability to explain complex AI concepts to non-technical stakeholders
• (Desirable) Bachelor’s Degree in Computer Science, Engineering, or a related field

What the job involves

• We are looking for a Senior Software Engineer to help build agentic systems that would automate workflows for different internal functional departments at Aircall
• This role combines deep software engineering skills with a desire to understand and automate workflows of stakeholders across Marketing, Sales, Customer Support, Customer Success, Finance, HR, Legal, Engineering, Product and many other functional areas using AI agents
• Partner with internal stakeholders to understand their daily workflows to surface and document those that can be automated with AI
• Build autonomous and semi-autonomous agent workflows that interact with browsers, codebases, and APIs to complete complex content operations
• Learn and contribute to prompt engineering strategies, with guidance on building agentic workflows, memory systems, and multi-step reasoning
• Build and operate MCP Servers that can be called by AI Agents
• Design and build proprietary agent libraries, prompting strategies and benchmarking frameworks
• Build and operationalize AI solutions with retrieval techniques (e.g., RAG, vector DBs) for context-aware applications
• Prototype, test, and optimize AI-powered applications, including retrieval-augmented generation, workflow automation, and agentic experiences
• Collaborate with cross-functional teams to align AI features with user needs and business goals, gaining exposure to product and platform thinking
• Stay current on advancements in AI technologies, frameworks, and best practices, and evangelize AI capabilities internally and externally
• Provide technical support, documentation, and training to facilitate adoption and effective use of AI solutions
• Participate in technical discussions, architecture reviews, and sprint planning
• Contribute to knowledge sharing and technical documentation