AI Agent Developer | Python, LangChain, Cloud (AWS), Autonomous Systems
Indexed description
Software Requirements
Required:
- Strong hands-on experience with Python for AI development, automation, and integration tasks.
- Deep understanding of agent-based AI frameworks, such as AgentCore, LangChain, or equivalent.
- Strong proficiency with cloud platforms, especially AWS, for deploying and managing AI solutions.
- Hands-on experience creating scalable, secure, and autonomous AI systems.
- Familiarity with APIs, REST, and data integration techniques.
- Experience with containerization tools such as Docker and orchestration platforms like Kubernetes.
- Experience with serverless architectures such as AWS Lambda.
- Knowledge of enterprise data storage including relational and NoSQL databases.
- Exposure to DevOps practices, CI/CD pipelines, and infrastructure automation tools.
- Familiarity with AI/ML libraries such as TensorFlow, PyTorch, or DeepResearch stacks.
- Lead the design, implementation, and deployment of autonomous agent-based AI systems utilizing Python and cloud platforms.
- Mentor and guide teams working on agentic AI projects, ensuring adherence to best practices and standards.
- Explore and evaluate emerging AI technologies and frameworks for potential adoption in strategic initiatives.
- Collaborate with product, data science, engineering, and architecture teams to define requirements and formulate scalable, secure AI solutions.
- Develop and maintain technical roadmaps aligned with organizational AI strategy.
- Oversee integration of agent-based systems with enterprise data, APIs, and other business-critical systems.
- Ensure AI system security, reliability, and explainability, adhering to governance and compliance standards.
Technical Skills (By Category)
Programming Languages:
- Essential: Python (advanced proficiency in AI and automation)
- Preferred: Java, C++, or other languages for systems integration
- Essential: AgentCore, LangChain, TensorFlow, PyTorch, DeepResearch (or similar)
- Preferred: Reinforcement learning tools, custom agent frameworks
- Essential: AWS (EC2, Lambda, S3, API Gateway, EKS)
- Preferred: Azure, GCP, cloud-native AI deployment
- Knowledge of relational (SQL) and NoSQL (DynamoDB, MongoDB) databases for data storage and retrieval.
- Essential: Docker, Kubernetes, CI/CD pipelines (such as GitHub Actions, TeamCity)
- Preferred: Infrastructure as Code (Terraform, CloudFormation)
- Understanding of security practices concerning data privacy, model security, and AI governance frameworks.
- Minimum of 8+ years supporting AI/ML projects, with substantial experience building agent-based systems.
- Proven experience designing, deploying, and managing autonomous AI architectures at enterprise scale.
- Demonstrated success leading cross-functional teams on AI initiatives from conception to production.
- Industry experience in finance, healthcare, or enterprise IT solutions is preferred; relevant R&D or academic project experience is acceptable.
- Architect, develop, and deploy agent-based AI systems, leveraging Python and cloud platforms.
- Lead teams through technical design, implementation, testing, and deployment phases.
- Collaborate closely with stakeholders to align AI solutions with strategic goals and compliance standards.
- Explore and suggest new frameworks and technologies for autonomous AI capabilities.
- Monitor, troubleshoot, and optimize AI systems, ensuring operational performance and security.
- Document system architecture, agent behaviors, and deployment procedures.
- Facilitate code reviews, knowledge sharing, and process improvements.
- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related fields.
- 8+ years of experience in AI development, with a focus on agent-based systems and cloud deployment.
- Relevant certifications in cloud platforms or AI frameworks are a plus.
- Strong analytical, problem-solving, and leadership skills.
- Excellent communication skills for stakeholder engagement and technical documentation.
- Critical thinking and innovative problem-solving in complex agent systems.
- Leadership qualities to guide and mentor technical teams.
- Effective communication of AI concepts to non-technical stakeholders.
- Ability to adapt swiftly to emerging AI frameworks and cloud technologies.
- Ownership of project outcomes, emphasizing security, reliability, and scalability.
- Time and resource management to deliver strategic AI projects on schedule.
All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.
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