Job Opportunities

Software AI Engineer

Software Engineer, AI Engineer
Must-Have Skills:
4+ years of experience in software engineering, backend engineering, or applied AI
engineering.
Strong programming skills in Java and/or Python.
Hands-on experience building AI-powered applications or integrating LLM capabilities into
production systems.
Experience designing or building AI agents, multi-step orchestration workflows, or toolusing automation systems.
Experience with MCP or similar integration patterns for connecting AI systems to external
tools, APIs, or enterprise platforms.
Strong understanding of system design, APIs, distributed systems, and production
software engineering fundamentals.
Familiarity with prompt design, context management, evaluation approaches, and
reliability patterns for agent-based systems.
Proven ability to work effectively in fast-paced delivery environments.
Delivery-oriented and comfortable operating across development, experimentation, and
production support responsibilities.
Effective at collaborating with cross-functional teams under tight timelines.
Strong ownership mindset with practical problem-solving skills.
Nice-to-Have Skills:
Experience with multi-agent systems, retrieval-augmented generation, semantic search,
or vector-based architectures.
Familiarity with cloud-native infrastructure, monitoring, and observability for AI services.
Experience with model evaluation, guardrails, safety patterns, and prompt/version
lifecycle management.
Experience integrating AI solutions with enterprise platforms such as Salesforce, Jira,
Slack, or internal developer tools.
Background in workflow automation, event-driven systems, or backend platforms that
support AI-enabled products.
Description: Scope of Work:
This contract Software Engineer supports AI engineering initiatives focused on building and
scaling intelligent applications, agentic workflows, and MCP-integrated solutions. The role
is suited for an engineer who can quickly contribute to AI-powered systems, productiongrade backend services, and applied automation use cases. The goal is to accelerate the
delivery of scalable AI solutions that improve developer productivity, workflow
orchestration, decision support, and downstream business integrations.
Key Responsibilities:
Design, build, and enhance AI-powered applications and backend services for internal or
customer-facing use cases.
Build and maintain AI agents and agentic workflows that can reason, orchestrate tasks,
and integrate with enterprise tools and services.
Develop MCP-based integrations and tool interfaces that enable AI systems to interact
securely with external platforms, APIs, and business systems.
Implement prompt orchestration, context handling, tool calling, memory patterns, and
evaluation workflows for reliable agent behavior.
Collaborate with engineering, product, and architecture teams to define scalable patterns
for AI agent development and deployment.
Integrate LLM capabilities into software systems while balancing performance, reliability,
cost, and safety.
Investigate system issues, improve quality and observability, and optimize AI workflow
efficiency in production environments.
Participate in code reviews, release support, experimentation, and production incident
resolution.
Create technical documentation and contribute to best practices for AI engineering, agent
development, and MCP adoption.
Time Zone Coverage: U.S. Central Time (CST); some overlap with India Standard Time (IST)
is expected (Preferably, availability until 11:00 a.m. CST)
Preferred Region: APAC