The job, in the employer's words
About the company
Our client is a fast-growing software company.
The role
Raydar is recruiting for this role on behalf of our client. Own the full lifecycle of web and AI-driven features, from understanding a customer need through design, implementation, deployment and production monitoring. The work spans front-end and back-end development with a strong emphasis on applied machine learning, including conversational agents and the testing that keeps them reliable. You will also use product judgment to decide what is worth building.
What you'll do
- Ship features end-to-end on a frequent cadence, working with customers to scope problems, building across the stack and monitoring behavior after release.
- Build conversational agents that handle voice and email interactions, including speech processing, language model orchestration and rule-based safeguards for critical details.
- Create an evaluation framework with curated test datasets, offline and online checks, regression testing and accuracy validation.
- Develop retrieval and matching capabilities tuned for cost and latency at scale.
- Set up monitoring and diagnostics that serve engineers, product stakeholders and customers.
- Distinguish one-off customer requests from broader signals worth building around.
Requirements
What we're looking for
- 5+ years of professional software engineering experience with end-to-end ownership across a full stack, including Python and TypeScript/React.
- Hands-on experience taking language model features into production, including architecture, tool use and retrieval.
- Fluency in evaluating and testing AI systems to confirm correctness before users report problems.
- Solid grounding in system design, including real-time data handling, parallel processing, databases and weighing performance against cost.
- Experience with agent or voice tooling, or comparable frameworks.
- Familiarity with monitoring live systems and releasing changes safely.
- Strong product instincts and comfort bridging customer needs with technical execution.
- Comfort with ambiguity, high-stakes decisions on limited data, and a highly autonomous remote environment.
- Daily use of generative AI coding tools, with the ability to verify their output.
Bonus points
- Experience with voice or real-time systems, including speech technology, latency management and telephony.
- Founding or early-stage engineering background.
- Familiarity with functional languages or hardware description languages.
- Experience with multi-agent orchestration or other complex tool-use systems.
- A track record of public code contributions or self-directed projects with broad usage.
Benefits
Compensation and benefits
- Base salary: USD 60,000 to 108,000 per year
Location and work model
- Remote (India)
- Full-time
Benefits mentioned
- Compensation and benefits
- - Base salary: USD 60,000 to 108,000 per year
- Location and work model
- - Remote (India)
- - Full-time
Requirements mentioned
- What we're looking for
- - 5+ years of professional software engineering experience with end-to-end ownership across a full stack, including Python and TypeScript/React.
- - Hands-on experience taking language model features into production, including architecture, tool use and retrieval.
- - Fluency in evaluating and testing AI systems to confirm correctness before users report problems.
- - Solid grounding in system design, including real-time data handling, parallel processing, databases and weighing performance against cost.
- - Experience with agent or voice tooling, or comparable frameworks.
- - Familiarity with monitoring live systems and releasing changes safely.
- - Strong product instincts and comfort bridging customer needs with technical execution.
- - Comfort with ambiguity, high-stakes decisions on limited data, and a highly autonomous remote environment.
- - Daily use of generative AI coding tools, with the ability to verify their output.
- Bonus points
- - Experience with voice or real-time systems, including speech technology, latency management and telephony.
- - Founding or early-stage engineering background.
- - Familiarity with functional languages or hardware description languages.
- - Experience with multi-agent orchestration or other complex tool-use systems.
- - A track record of public code contributions or self-directed projects with broad usage.
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