Role: Intermediate Cloud / AI Developer
Location: Washington, DC/ Remote
Duration: 12 months
Client: Infosys public services / United States Postal Service
Note: candidates must meet the residency requirements (Last 5 years in the US with no more
than 6 months out of the country).
Intermediate Cloud / Artificial Intelligence (AI) Developer designs, develops, tests, and
supports Java-based, cloud-native applications on the Google Cloud Platform (Google Cloud Platform)
that enable and improve business workflows. This role builds secure, scalable services
with increasing independence, contributes to technical design and implementation
decisions, and collaborates closely with DevOps, Quality Assurance (QA), Product
Management, and security partners to deliver reliable solutions that meet performance,
security, and compliance expectations.
Required Skills
Minimum of 7 years of software development experience (or equivalent
demonstrated capability).
Bachelor’s degree from an accredited college/university in Computer Science,
Engineering, or a related field is preferred (or equivalent practical experience).
5 years of experience developing backend applications or services in Java.
Hands-on experience working with cloud services and deploying applications on
Google Cloud Platform (or equivalent cloud experience with the ability to ramp quickly).
Experience designing and implementing REST APIs, including common
authentication/authorization approaches and integration patterns.
Experience integrating AI capabilities into applications (for example: calling AI
APIs/services for summarization, extraction, classification, or decision support)
and familiarity with basic evaluation/monitoring concepts.
Practical knowledge of secure engineering fundamentals (least privilege access,
secrets management, encryption, and audit logging).
Proficiency with Git-based workflows and working knowledge of CI/CD concepts
and release practices.
Strong troubleshooting skills, including defect triage, performance tuning, and
supporting applications with observability tools.
Strong communication and collaboration skills across engineering, QA, DevOps,
product, and security stakeholders.
Preferred Qualifications
Experience working in Agile teams and applying Software Development Life
Cycle (SDLC) practices.
Familiarity with change/configuration management tools (for example:
VersionOne, ServiceNow) and/or Application Lifecycle Management (ALM)
practices.
Experience with container and/or serverless concepts (for example: Docker,
Kubernetes fundamentals, or managed/serverless deployments).
Experience participating in production support rotations and contributing to post-
incident analysis and corrective actions.
Key Responsibilities
Design, develop, and maintain Java backend services using modern engineering
practices, established patterns, and reusable components.
Build and enhance cloud-based solutions on Google Cloud Platform that support data ingestion,
processing, storage, retrieval, and distribution; contribute to solution design for
reliability and performance.
Develop and maintain Representational State Transfer (REST) application
programming interfaces (APIs), including versioning, documentation, backward
compatibility, and integration with internal and external systems.
Implement AI-enabled features by integrating approved AI services or models
into applications; contribute to basic evaluation and monitoring approaches to
ensure quality and responsible use.
Independently troubleshoot and resolve application issues across environments,
perform root-cause analysis, and implement preventative fixes to reduce repeat
incidents.
Apply secure coding practices and ensure solutions meet security and
compliance requirements (for example: authentication/authorization, encryption
in transit and at rest, audit logging, and policy-aligned data handling).
Contribute to continuous integration/continuous delivery (CI/CD) pipelines and
deployment automation in partnership with DevOps to improve release quality
and repeatability.
Implement and maintain observability practices including structured logging,
metrics, dashboards, alerts, and operational documentation/runbooks.
Collaborate with cross-functional partners to plan and deliver releases, support
testing, and resolve production issues as needed.
Participate in and contribute to architecture/design discussions and code
reviews; help promote team standards and mentor junior developers through
guidance and example.
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