About the Role
Constelli Signals is looking for an AI Engineer to join and support the design, development, and deployment of AI-driven tools and systems across the organization. This role involves building knowledge management systems, workflow automation, AI agents, and intelligent enterprise solutions that improve productivity and decision-making.
The ideal candidate stays current with the rapidly evolving AI ecosystem and can translate emerging tools, frameworks, and techniques into secure, scalable, and cost-effective solutions. The role requires balancing innovation with practical implementation, ensuring high standards of data security, governance, reliability, and AI cost optimization.
Key Responsibilities
Knowledge & Information Systems
- Design and build AI-powered knowledge management systems to improve information accessibility and organizational productivity.
- Establish data cleaning, filtering, structuring, and formatting standards to ensure information is accurate, consistent, secure, and reusable.
- Conduct requirement gathering with cross-functional teams to identify high-value AI use cases before solution development.
- Support standardization of internal documentation, reporting formats, and knowledge repositories.
AI Automation & Workflow Integration
- Build, deploy, and maintain AI-powered workflows by integrating enterprise tools such as Microsoft 365, CRM platforms, and internal applications.
- Design, develop, and optimize AI agents and agentic workflows to automate business processes, knowledge retrieval, reporting, documentation, scheduling, and decision support.
- Evaluate emerging AI models, agent frameworks, automation platforms, and orchestration tools for reliability, scalability, security, and business value.
- Monitor production AI systems, continuously improving performance, accuracy, user adoption, and operational efficiency.
- Optimize AI infrastructure and model usage by selecting appropriate models, managing token consumption, improving inference efficiency, and reducing operational costs without compromising performance.
Research, Security & Governance
- Track advancements in AI models, LLMs, agent frameworks, RAG architectures, vector databases, and related technologies, assessing their applicability to the organization.
- Ensure AI solutions comply with organizational data security policies by implementing appropriate access controls, secure data handling practices, permission management, and governance mechanisms.
- Evaluate AI platforms from security, privacy, compliance, and enterprise readiness perspectives before deployment.
- Maintain technical documentation, architecture guidelines, evaluation frameworks, and best practices to support long-term knowledge continuity.
Cross-Functional Collaboration
- Work closely with business and technical teams to understand operational challenges and translate them into AI-enabled solutions.
- Collaborate with leadership to prioritize AI initiatives aligned with organizational objectives.
- Support strategic AI initiatives, pilots, and emerging technology projects as required.
- Communicate technical concepts effectively to both technical and non-technical stakeholders.
Required Skills & Qualifications
- 2–4 years of hands-on experience working with LLMs, AI agent frameworks, RAG pipelines, vector databases, and enterprise AI applications.
- Practical experience with LLM APIs (Claude, OpenAI, Gemma or equivalent), including function calling, tool integration, prompt engineering, and orchestration.
- Experience building AI agents and integrating AI solutions with SaaS platforms and enterprise applications through APIs and webhooks.
- Good understanding of AI security, enterprise data governance, privacy, access control, and secure deployment practices.
- Experience evaluating AI models based on performance, latency, security, and cost, with an ability to optimize AI infrastructure and operational expenses.
- Strong analytical, problem-solving, and research skills with the ability to independently evaluate emerging AI technologies.
- Excellent communication and stakeholder management skills with the ability to work across technical and business teams.
- Experience in regulated industries such as defense, aerospace, healthcare, or financial services, and exposure to enterprise AI governance or security frameworks, will be an added advantage.
- Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent practical experience).
What We Offer
- Opportunity to work on high-impact AI initiatives with direct visibility to leadership.
- Ownership of meaningful projects involving AI agents, enterprise automation, and next-generation AI technologies.
- A collaborative, fast-paced environment focused on continuous learning and innovation.
- Exposure to advanced technology domains within the defense and aerospace sector.
