Job Description

Job Opportunity: Senior AI Software Developer

Overview

We are seeking a highly skilled and experienced Senior AI Software Developer to join our dynamic team. This hybrid role offers the flexibility to work remotely while spending an average of two days per week in the office. As a Senior AI Software Developer, you will play a pivotal role in designing, developing, and deploying cutting-edge AI solutions that drive innovation and deliver exceptional value. If you are passionate about artificial intelligence, have a strong background in software development, and thrive in a collaborative environment, we encourage you to apply.

Responsibilities

As a Senior AI Software Developer, you will be responsible for:

Solution Engineering & Delivery

• Translating high-level designs into clear component contracts, APIs, and service boundaries.
• Implementing LLM integrations, RAG pipelines, agents, tool/function calling, and prompt strategies.
• Owning feature delivery for sprints/releases while maintaining high code quality and documentation.

Modeling & Evaluation

• Fine-tuning models as needed and designing evaluation harnesses and metrics.
• Building A/B testing setups and tracking accuracy, latency, robustness, and task success rates.
• Conducting error analysis and iterating using feedback efficacy loops and prompt refinement.

Data & Retrieval Engineering

• Building ETL/ELT pipelines and curating datasets with metadata, lineage, and validation.
• Implementing vector indexing, tuning chunk size and overlap, and enforcing data governance.

MLOps & Platform Readiness

• Containerizing workloads using Docker and orchestrating deployments with Kubernetes/Helm.
• Managing CI/CD pipelines for machine learning workflows, including training, evaluation, packaging, deployment, monitoring, and rollback.
• Maintaining model/agent registries, experiment tracking, and reproducible environments.

Software Engineering & Integration

• Developing microservices and asynchronous inference paths to support batch/stream processing.
• Integrating enterprise authentication, observability, telemetry, and logging.
• Writing unit, integration, end-to-end tests, performance benchmarks, and failure-injection tests.

Observability, Reliability & Performance

• Instrumenting systems with metrics, logs, and traces while defining SLOs for latency, throughput, and error rates.
• Optimizing inference through batching, caching, quantization, and token efficiency.
• Implementing guardrails, safety filters, jailbreak detection, auto-evaluations, and alerts.

Security & Compliance

• Applying secure coding practices and managing secrets, encryption, and least privilege access.
• Ensuring compliance with data residency, consent, and audit trail requirements.
• Enforcing policy-based access and content safety in user-facing features.

Collaboration & Mentoring

• Reviewing designs and pull requests while coaching junior engineers on best practices.
• Collaborating with AI Architects, Data Engineers, QA teams, and Product Managers.

Qualifications

Education & Experience

• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, Machine Learning, Artificial Intelligence, or a closely related quantitative discipline.
• 7-10 years of relevant experience in software development and AI engineering.

Technical Skills

• Expertise in LLMs, agents, prompt engineering, and orchestration frameworks.
• Strong knowledge of machine learning evaluation metrics, error analysis, and data engineering.
• Proficiency in Python (FastAPI/Flask) and microservices architecture.
• Experience with MLOps tools such as Docker, Kubernetes, CI/CD pipelines, and GPU scheduling.
• Familiarity with frameworks like PyTorch, TensorFlow, Hugging Face, LangChain, and LlamaIndex.
• Hands-on experience with vector databases (e.g., FAISS, Milvus, Pinecone) and data processing tools (e.g., Pandas, SQL/NoSQL, Kafka).

Additional Skills

• Strong understanding of artificial intelligence technologies, data science, and machine learning operations.
• A security-first mindset with experience in scalability testing and compliance.
• Excellent collaboration, communication, and mentoring abilities.

Day-to-Day

• Collaborate with cross-functional teams to design and implement AI-driven solutions.
• Develop, test, and deploy scalable and secure AI models and microservices.
• Monitor system performance, troubleshoot issues, and optimize AI workflows.
• Mentor junior team members and contribute to the continuous improvement of engineering practices.
• Stay updated on the latest advancements in AI and machine learning technologies.