Guide the technical vision and strategy, making high-level architectural decisions.
Provide technical expertise and contribute to corporate strategy and technology recommendations.
Collaborate with cross-functional teams to translate business requirements into scalable software solutions.
Design and implement complex, fault-tolerant software systems, adhering to best practices in software architecture, coding standards, and design patterns.
Develop and maintain Python-based applications, libraries, and microservices using modern frameworks and tools.
Participate in code reviews to ensure quality, maintainability, and consistency.
Mentor and guide junior developers and data scientists, fostering a culture of continuous learning.
Implement automated testing strategies to ensure code reliability and performance.
Stay current with emerging trends, technologies, and best practices in the Python ecosystem.
Represent the engineering team in technical discussions and decision-making processes.
Resolve complex technical issues and serve as an escalation point for development problems.
Design and manage complex data models and data workflows.
Carry out management responsibilities, including interviewing, hiring, training, performance evaluation, and conflict resolution.
Promote accountability, innovation, and ownership among team members.
Architect and optimize data storage and retrieval systems (structured and unstructured, e.g., S3).
Build and integrate vector databases (e.g., Pinecone, Weaviate, FAISS) and search technologies (e.g., Solr, Elasticsearch, OpenSearch).
Design and deploy messaging systems (e.g., AWS SNS) for asynchronous and streaming workloads.
Monitor system and application health in real time to ensure uptime and performance.
Implement and manage access control mechanisms (IAM, OAuth2, RBAC, Vault, or AWS Secrets Manager).
Act as a liaison between software engineering, data science, and DevOps teams.
Standardize workflows and tools across research, dev, and production environments.
Contribute to sprint planning, architectural design sessions, backlog grooming, and post-mortems.
Design and implement caching strategies and low-latency data access layers to accelerate model inference and data APIs.
Perform other duties as assigned.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or related field (or equivalent experience)
Several years of professional software development experience, with a strong emphasis on Python
Extensive experience with frameworks such as Django, Flask, or FastAPI
Familiarity with retrieval-augmented generation (RAG) pipelines and scalable AI systems
Proficiency in relational and non-relational databases, including ORM frameworks like SQLAlchemy
Expertise in Docker, Kubernetes, and cloud platforms (AWS, Azure, or GCP)
Experience designing APIs and data-driven systems
Strong understanding of CI/CD pipelines and version control (Git)
Experience leading projects and mentoring teams
Excellent problem-solving, communication, and leadership skills
Experience working with cache and in-memory databases (e.g., Redis, Memcached)
Familiarity with observability stacks (EFK/ELK, Prometheus, Datadog, Grafana) and distributed tracing (OpenTelemetry)
Experience with messaging systems (AWS SNS, Kafka)
Solid understanding of IAM, RBAC, and secrets management
Proficiency in integrating LangChain or similar frameworks for modular AI workflows.

Benefits

numerous wellbeing initiatives
shared parental leave
study assistance
sabbaticals
annual incentive bonus

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills

PythonDjangoFlaskFastAPIDockerKubernetesAWSCI/CDGitSQLAlchemy

Soft skills

problem-solvingcommunicationleadershipmentoringcollaborationaccountabilityinnovationownershipconflict resolutioncontinuous learning