AI Engineer – L1 ( Exp: 1 )

Responsibilities

• Build and ship well-scoped features across the stack – backend services, APIs, frontend interfaces, and data layers – taking each from implementation through testing and deployment, with guidance from senior engineers.
• Contribute to the platform services that power voice AI at scale: campaign orchestration, dialer logic, call routing, scheduling, and the integrations that tie telephony to the application layer.
• Learn to write code that holds up in production – handling errors gracefully, respecting performance constraints, and improving reliability as you go.
• Work with data models, queries, and pipelines (PostgreSQL, time-series and CDR data) to support call processing, reporting, and analytics.
• Debug issues across the stack with growing independence – reading logs, reproducing problems, and tracing whether a failure comes from application code, the database, an integration, or infrastructure.
• Integrate third-party services and provider APIs (telephony, LLM/ASR/TTS, messaging, payments) into features, learning to handle errors, rate limits, and retries robustly.
• Build features with scale and resilience in mind, learning patterns for concurrency, retries, and graceful degradation under production load.
• Follow and absorb the team’s engineering best practices around code quality, testing, version control, and CI/CD – and steadily raise your own bar.
• Communicate clearly in code reviews, design discussions, and documentation, asking good questions and surfacing blockers early.

Desired Profile

• 1+ years of experience building software (strong internships, substantial personal/academic projects, or open-source contributions count toward this).
• Hands-on experience writing backend services or APIs, with some exposure to frontend work.
• Working knowledge of Python; familiarity with Django (or a similar web framework) is a plus.
• Comfortable using AI coding and productivity tools (e.g. Claude Code, Cursor, Copilot) and eager to make them a core part of how you build and ship.
• Familiarity with relational databases (PostgreSQL preferred) – writing queries, understanding basic schema design, and working with real data.
• Some exposure to or genuine curiosity about cloud infrastructure (AWS preferred — EC2, RDS/Aurora, S3) and concepts like deployment, containerization, and CI/CD.
• A developing debugging mindset – willing to dig into logs, trace a request, and figure out where something broke instead of guessing.
• Clear written communication for code reviews, design notes, and documentation.
• Curious, coachable, and a fast learner, motivated by shipping real products used by real customers and by feedback that helps you grow.

Bonus if you have experience in:

• DevOps practices and tooling, CI/CD pipelines, containerization (Docker), or managing deployments across environments.
• FreeSWITCH or similar telephony platforms, or even a working understanding of how an application layer integrates with a voice stack.
• AWS data services such as Glue and Athena, or any experience building ETL pipelines and querying large-scale data.
• Building dashboards and reporting layers that turn operational data into useful insight.
• Security and compliance basics in production systems, especially for regulated (BFSI) clients.
• Telephony/SIP, real-time systems, or other latency-sensitive production infrastructure.